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ORCIDYoshua Bengio
Person information
- affiliation: University of Montréal, Department of Computer Science and Operations Research, QC, Canada
- award (2018): Turing Award
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2020 – today
- 2025
[c467]Lazar Atanackovic, Xi Zhang, Brandon Amos, Mathieu Blanchette, Leo J. Lee, Yoshua Bengio, Alexander Tong, Kirill Neklyudov:
Meta Flow Matching: Integrating Vector Fields on the Wasserstein Manifold. ICLR 2025- [c466]Oussama Boussif, Léna Néhale Ezzine, Joseph D. Viviano, Michal Koziarski, Moksh Jain, Nikolay Malkin, Emmanuel Bengio, Rim Assouel, Yoshua Bengio:
Action abstractions for amortized sampling. ICLR 2025 - [c465]Aniket Rajiv Didolkar, Andrii Zadaianchuk, Anirudh Goyal, Michael Curtis Mozer, Yoshua Bengio, Georg Martius, Maximilian Seitzer:
On the Transfer of Object-Centric Representation Learning. ICLR 2025 - [c464]Hongyu Guo, Yoshua Bengio, Shengchao Liu:
AssembleFlow: Rigid Flow Matching with Inertial Frames for Molecular Assembly. ICLR 2025 - [c463]Zhen Liu, Tim Z. Xiao, Weiyang Liu, Yoshua Bengio, Dinghuai Zhang:
Efficient Diversity-Preserving Diffusion Alignment via Gradient-Informed GFlowNets. ICLR 2025 - [i557]Diego A. Velázquez, Pau Rodríguez López, Sergio Alonso, Josep M. Gonfaus, Jordi Gonzàlez
, Gerardo Richarte, Javier Marin, Yoshua Bengio, Alexandre Lacoste:
EarthView: A Large Scale Remote Sensing Dataset for Self-Supervision. CoRR abs/2501.08111 (2025) - [i556]David Williams-King, Linh Le, Adam Oberman, Yoshua Bengio:
Can Safety Fine-Tuning Be More Principled? Lessons Learned from Cybersecurity. CoRR abs/2501.11183 (2025) - [i555]Yoshua Bengio, Sören Mindermann, Daniel Privitera, Tamay Besiroglu, Rishi Bommasani, Stephen Casper, Yejin Choi, Philip Fox, Ben Garfinkel, Danielle Goldfarb, Hoda Heidari, Anson Ho, Sayash Kapoor, Leila Khalatbari, Shayne Longpre, Sam Manning, Vasilios Mavroudis, Mantas Mazeika, Julian Michael, Jessica Newman, Kwan Yee Ng, Chinasa T. Okolo, Deborah Raji, Girish Sastry, Elizabeth Seger, Theodora Skeadas, Tobin South, Emma Strubell, Florian Tramèr, Lucia Velasco, Nicole Wheeler, Daron Acemoglu, Olubayo Adekanmbi, David Dalrymple, Thomas G. Dietterich, Edward W. Felten, Pascale Fung, Pierre-Olivier Gourinchas, Fredrik Heintz, Geoffrey E. Hinton, Nick R. Jennings, Andreas Krause, Susan Leavy, Percy Liang, Teresa Ludermir, Vidushi Marda, Helen Margetts, John A. McDermid, Jane Munga, Arvind Narayanan, Alondra Nelson, Clara Neppel, Alice Oh, Gopal Ramchurn, Stuart Russell, Marietje Schaake, Bernhard Schölkopf, Dawn Song, Alvaro Soto, Lee Tiedrich, Gaël Varoquaux, Andrew Yao, Ya-Qin Zhang, Fahad Albalawi, Marwan Alserkal, Olubunmi Ajala, Guillaume Avrin, Christian Busch, André Carlos Ponce de Leon Ferreira de Carvalho, Bronwyn Fox, Amandeep Singh Gill, Ahmet Halit Hatip, Juha Heikkilä, Gill Jolly, Ziv Katzir, Hiroaki Kitano, Antonio Krüger, Chris Johnson, Saif M. Khan, Kyoung Mu Lee, Dominic Vincent Ligot, Oleksii Molchanovskyi, Andrea Monti, Nusu Mwamanzi, Mona Nemer, Nuria Oliver, José Ramón López Portillo, Balaraman Ravindran, Raquel Pezoa Rivera, Hammam Riza, Crystal Rugege, Ciarán Seoighe, Jerry Sheehan, Haroon Sheikh, Denise Wong, Yi Zeng:
International AI Safety Report. CoRR abs/2501.17805 (2025) - [i554]Ahmed Masry, Juan A. Rodriguez, Tianyu Zhang, Suyuchen Wang, Chao Wang, Aarash Feizi, Akshay Kalkunte Suresh, Abhay Puri, Xiangru Jian, Pierre-André Noël, Sathwik Tejaswi Madhusudhan, Marco Pedersoli, Bang Liu, Nicolas Chapados, Yoshua Bengio, Enamul Hoque, Christopher Pal, Issam H. Laradji, David Vázquez, Perouz Taslakian, Spandana Gella, Sai Rajeswar:
AlignVLM: Bridging Vision and Language Latent Spaces for Multimodal Understanding. CoRR abs/2502.01341 (2025) - [i553]Ivan Grega, Félix Therrien, Abhishek Soni, Karry Ocean, Kevan Dettelbach, Ribwar Ahmadi, Mehrdad Mokhtari, Curtis P. Berlinguette, Yoshua Bengio:
A physics-based data-driven model for CO2 gas diffusion electrodes to drive automated laboratories. CoRR abs/2502.06323 (2025) - [i552]Siddarth Venkatraman, Mohsin Hasan, Minsu Kim, Luca Scimeca, Marcin Sendera, Yoshua Bengio, Glen Berseth, Nikolay Malkin:
Outsourced diffusion sampling: Efficient posterior inference in latent spaces of generative models. CoRR abs/2502.06999 (2025) - [i551]Jaesik Yoon, Hyeonseo Cho, Doojin Baek, Yoshua Bengio, Sungjin Ahn:
Monte Carlo Tree Diffusion for System 2 Planning. CoRR abs/2502.07202 (2025) - [i550]Thomas Jiralerspong, Berton Earnshaw, Jason S. Hartford, Yoshua Bengio, Luca Scimeca:
Shaping Inductive Bias in Diffusion Models through Frequency-Based Noise Control. CoRR abs/2502.10236 (2025) - [i549]Sarthak Mittal, Yoshua Bengio, Nikolay Malkin, Guillaume Lajoie:
In-Context Parametric Inference: Point or Distribution Estimators? CoRR abs/2502.11617 (2025) - [i548]Félix Therrien, Jamal Abou Haibeh, Divya Sharma, Rhiannon Hendley, Alex Hernández-García, Sun Sun, Alain Tchagang, Jiang Su, Samuel Huberman, Yoshua Bengio, Hongyu Guo, Homin Shin:
OBELiX: A Curated Dataset of Crystal Structures and Experimentally Measured Ionic Conductivities for Lithium Solid-State Electrolytes. CoRR abs/2502.14234 (2025) - [i547]Yoshua Bengio, Michael K. Cohen, Damiano Fornasiere, Joumana Ghosn, Pietro Greiner, Matt MacDermott, Sören Mindermann, Adam Oberman, Jesse Richardson, Oliver Richardson, Marc-Antoine Rondeau, Pierre-Luc St-Charles, David Williams-King:
Superintelligent Agents Pose Catastrophic Risks: Can Scientist AI Offer a Safer Path? CoRR abs/2502.15657 (2025) - [i546]Mohammed Mahfoud, Ghait Boukachab, Michal Koziarski, Alex Hernández-García, Stefan Bauer, Yoshua Bengio, Nikolay Malkin:
Learning Decision Trees as Amortized Structure Inference. CoRR abs/2503.06985 (2025) - [i545]Luca Scimeca, Siddarth Venkatraman, Moksh Jain, Minsu Kim, Marcin Sendera, Mohsin Hasan, Luke Rowe, Sarthak Mittal, Pablo Lemos, Emmanuel Bengio, Alexandre Adam, Jarrid Rector-Brooks, Yashar Hezaveh, Laurence Perreault Levasseur, Yoshua Bengio, Glen Berseth, Nikolay Malkin:
Solving Bayesian inverse problems with diffusion priors and off-policy RL. CoRR abs/2503.09746 (2025) - [i544]Minsu Kim, Jiayao Gu, Ye Yuan, Taeyoung Yun, Zixuan Liu, Yoshua Bengio, Can Chen:
Offline Model-Based Optimization: Comprehensive Review. CoRR abs/2503.17286 (2025) - [i543]Brian R. Bartoldson, Siddarth Venkatraman, James Diffenderfer, Moksh Jain, Tal Ben-Nun, Seanie Lee, Minsu Kim, Johan Obando-Ceron, Yoshua Bengio, Bhavya Kailkhura:
Trajectory Balance with Asynchrony: Decoupling Exploration and Learning for Fast, Scalable LLM Post-Training. CoRR abs/2503.18929 (2025) - [i542]Paul Bertin, Joseph D. Viviano, Alejandro Tejada-Lapuerta, Weixu Wang, Stefan Bauer, Fabian J. Theis, Yoshua Bengio:
A scalable gene network model of regulatory dynamics in single cells. CoRR abs/2503.20027 (2025) - [i541]Chang Chen, Hany Hamed, Doojin Baek, Taegu Kang, Yoshua Bengio, Sungjin Ahn:
Extendable Long-Horizon Planning via Hierarchical Multiscale Diffusion. CoRR abs/2503.20102 (2025) - [i540]Mélisande Teng, Arthur Ouaknine, Etienne Laliberté, Yoshua Bengio, David Rolnick, Hugo Larochelle:
Assessing SAM for Tree Crown Instance Segmentation from Drone Imagery. CoRR abs/2503.20199 (2025) - 2024
- [j127]Alistair Knott, Dino Pedreschi, Toshiya Jitsuzumi, Susan Leavy, David M. Eyers, Tapabrata Chakraborti, Andrew Trotman, Sundar Sundareswaran, Ricardo Baeza-Yates, Przemyslaw Biecek, Adrian Weller, Paul D. Teal, Subhadip Basu, Mehmet Haklidir, Virginia Morini, Stuart Russell, Yoshua Bengio:
AI content detection in the emerging information ecosystem: new obligations for media and tech companies. Ethics Inf. Technol. 26(4): 63 (2024) - [j126]Alistair Knott, Dino Pedreschi, Toshiya Jitsuzumi, Susan Leavy, David M. Eyers, Tapabrata Chakraborti, Andrew Trotman, Sundar Sundareswaran, Ricardo Baeza-Yates, Przemyslaw Biecek, Adrian Weller, Paul D. Teal, Subhadip Basu, Mehmet Haklidir, Virginia Morini, Stuart Russell, Yoshua Bengio:
Correction: AI content detection in the emerging information ecosystem: new obligations for media and tech companies. Ethics Inf. Technol. 26(4): 71 (2024) - [j125]Alexandre Duval, Victor Schmidt, Santiago Miret, Yoshua Bengio, Alex Hernández-García, David Rolnick:
PhAST: Physics-Aware, Scalable, and Task-Specific GNNs for Accelerated Catalyst Design. J. Mach. Learn. Res. 25: 106:1-106:26 (2024) - [j124]Alexander Tong, Kilian Fatras, Nikolay Malkin, Guillaume Huguet, Yanlei Zhang, Jarrid Rector-Brooks, Guy Wolf, Yoshua Bengio:
Improving and generalizing flow-based generative models with minibatch optimal transport. Trans. Mach. Learn. Res. 2024 (2024) - [j123]Alex Hernández-García, Nikita Saxena, Moksh Jain, Cheng-Hao Liu, Yoshua Bengio:
Multi-Fidelity Active Learning with GFlowNets. Trans. Mach. Learn. Res. 2024 (2024) - [j122]Dinghuai Zhang, Ling Pan, Ricky T. Q. Chen, Aaron C. Courville, Yoshua Bengio:
Distributional GFlowNets with Quantile Flows. Trans. Mach. Learn. Res. 2024 (2024) - [c462]Xu Tan, Tao Qin, Jiang Bian, Tie-Yan Liu, Yoshua Bengio:
Regeneration Learning: A Learning Paradigm for Data Generation. AAAI 2024: 22614-22622 - [c461]Alexander Tong, Nikolay Malkin, Kilian Fatras, Lazar Atanackovic, Yanlei Zhang, Guillaume Huguet, Guy Wolf, Yoshua Bengio:
Simulation-Free Schrödinger Bridges via Score and Flow Matching. AISTATS 2024: 1279-1287 - [c460]Harry Zhao, Safa Alver, Harm van Seijen, Romain Laroche, Doina Precup, Yoshua Bengio:
Consciousness-Inspired Spatio-Temporal Abstractions for Better Generalization in Reinforcement Learning. ICLR 2024 - [c459]Aniket Rajiv Didolkar, Anirudh Goyal, Yoshua Bengio:
Cycle Consistency Driven Object Discovery. ICLR 2024 - [c458]Jean-Pierre R. Falet, Hae Beom Lee, Nikolay Malkin, Chen Sun, Dragos Secrieru, Dinghuai Zhang, Guillaume Lajoie, Yoshua Bengio:
Delta-AI: Local objectives for amortized inference in sparse graphical models. ICLR 2024 - [c457]Leo Feng, Frederick Tung, Hossein Hajimirsadeghi, Yoshua Bengio, Mohamed Osama Ahmed:
Tree Cross Attention. ICLR 2024 - [c456]Edward J. Hu, Moksh Jain, Eric Elmoznino, Younesse Kaddar, Guillaume Lajoie, Yoshua Bengio, Nikolay Malkin:
Amortizing intractable inference in large language models. ICLR 2024 - [c455]Marco Jiralerspong, Bilun Sun, Danilo Vucetic, Tianyu Zhang, Yoshua Bengio, Gauthier Gidel, Nikolay Malkin:
Expected flow networks in stochastic environments and two-player zero-sum games. ICLR 2024 - [c454]Minsu Kim, Taeyoung Yun, Emmanuel Bengio, Dinghuai Zhang, Yoshua Bengio, Sungsoo Ahn, Jinkyoo Park:
Local Search GFlowNets. ICLR 2024 - [c453]Amin Mansouri, Jason S. Hartford, Yan Zhang, Yoshua Bengio:
Object centric architectures enable efficient causal representation learning. ICLR 2024 - [c452]Ling Pan, Moksh Jain, Kanika Madan, Yoshua Bengio:
Pre-Training and Fine-Tuning Generative Flow Networks. ICLR 2024 - [c451]Dinghuai Zhang, Ricky T. Q. Chen, Cheng-Hao Liu, Aaron C. Courville, Yoshua Bengio:
Diffusion Generative Flow Samplers: Improving learning signals through partial trajectory optimization. ICLR 2024 - [c450]Ming-Yang Zhou, Zichao Yan, Elliot Layne, Nikolay Malkin, Dinghuai Zhang, Moksh Jain, Mathieu Blanchette, Yoshua Bengio:
PhyloGFN: Phylogenetic inference with generative flow networks. ICLR 2024 - [c449]Tara Akhound-Sadegh, Jarrid Rector-Brooks, Avishek Joey Bose, Sarthak Mittal, Pablo Lemos, Cheng-Hao Liu, Marcin Sendera, Siamak Ravanbakhsh, Gauthier Gidel, Yoshua Bengio, Nikolay Malkin, Alexander Tong:
Iterated Denoising Energy Matching for Sampling from Boltzmann Densities. ICML 2024 - [c448]Leo Feng, Frederick Tung, Hossein Hajimirsadeghi, Yoshua Bengio, Mohamed Osama Ahmed:
Memory Efficient Neural Processes via Constant Memory Attention Block. ICML 2024 - [c447]Minsu Kim, Joohwan Ko, Taeyoung Yun, Dinghuai Zhang, Ling Pan, Woochang Kim, Jinkyoo Park, Emmanuel Bengio, Yoshua Bengio:
Learning to Scale Logits for Temperature-Conditional GFlowNets. ICML 2024 - [c446]Pablo Lemos, Nikolay Malkin, Will Handley, Yoshua Bengio, Yashar Hezaveh, Laurence Perreault Levasseur:
Improving Gradient-Guided Nested Sampling for Posterior Inference. ICML 2024 - [c445]Milos Nikolic, Ghouthi Boukli Hacene, Ciaran Bannon, Alberto Delmas Lascorz, Matthieu Courbariaux, Omar Mohamed Awad, Isak Edo Vivancos, Yoshua Bengio, Vincent Gripon, Andreas Moshovos:
BitPruning: Learning Bitlengths for Aggressive and Accurate Quantization. ISCAS 2024: 1-5 - [c444]Aniket Didolkar, Anirudh Goyal, Nan Rosemary Ke, Siyuan Guo, Michal Valko, Timothy P. Lillicrap, Danilo Jimenez Rezende, Yoshua Bengio, Michael C. Mozer, Sanjeev Arora:
Metacognitive Capabilities of LLMs: An Exploration in Mathematical Problem Solving. NeurIPS 2024 - [c443]Michal Koziarski, Andrei Rekesh, Dmytro Shevchuk, Almer van der Sloot, Piotr Gainski, Yoshua Bengio, Cheng-Hao Liu, Mike Tyers, Robert A. Batey:
RGFN: Synthesizable Molecular Generation Using GFlowNets. NeurIPS 2024 - [c442]Marcin Sendera, Minsu Kim, Sarthak Mittal, Pablo Lemos, Luca Scimeca, Jarrid Rector-Brooks, Alexandre Adam, Yoshua Bengio, Nikolay Malkin:
Improved off-policy training of diffusion samplers. NeurIPS 2024 - [c441]Siddarth Venkatraman, Moksh Jain, Luca Scimeca, Minsu Kim, Marcin Sendera, Mohsin Hasan, Luke Rowe, Sarthak Mittal, Pablo Lemos, Emmanuel Bengio, Alexandre Adam, Jarrid Rector-Brooks, Yoshua Bengio, Glen Berseth, Nikolay Malkin:
Amortizing intractable inference in diffusion models for vision, language, and control. NeurIPS 2024 - [c440]Xi Zhang, Yuan Pu, Yuki Kawamura, Andrew Loza, Yoshua Bengio, Dennis L. Shung, Alexander Tong:
Trajectory Flow Matching with Applications to Clinical Time Series Modelling. NeurIPS 2024 - [c439]Tristan Deleu, Padideh Nouri, Nikolay Malkin, Doina Precup, Yoshua Bengio:
Discrete Probabilistic Inference as Control in Multi-path Environments. UAI 2024: 997-1021 - [i539]Thomas Jiralerspong, Xiaoyin Chen, Yash More, Vedant Shah, Yoshua Bengio:
Efficient Causal Graph Discovery Using Large Language Models. CoRR abs/2402.01207 (2024) - [i538]Marcin Sendera, Minsu Kim, Sarthak Mittal, Pablo Lemos, Luca Scimeca, Jarrid Rector-Brooks, Alexandre Adam, Yoshua Bengio, Nikolay Malkin:
On diffusion models for amortized inference: Benchmarking and improving stochastic control and sampling. CoRR abs/2402.05098 (2024) - [i537]Tara Akhound-Sadegh, Jarrid Rector-Brooks, Avishek Joey Bose, Sarthak Mittal, Pablo Lemos, Cheng-Hao Liu, Marcin Sendera, Siamak Ravanbakhsh, Gauthier Gidel, Yoshua Bengio, Nikolay Malkin, Alexander Tong:
Iterated Denoising Energy Matching for Sampling from Boltzmann Densities. CoRR abs/2402.06121 (2024) - [i536]Girish Sastry, Lennart Heim, Haydn Belfield, Markus Anderljung, Miles Brundage, Julian Hazell, Cullen O'Keefe, Gillian K. Hadfield, Richard Ngo, Konstantin Pilz, George Gor, Emma Bluemke, Sarah Shoker, Janet Egan, Robert F. Trager, Shahar Avin, Adrian Weller, Yoshua Bengio, Diane Coyle:
Computing Power and the Governance of Artificial Intelligence. CoRR abs/2402.08797 (2024) - [i535]Tristan Deleu, Padideh Nouri, Nikolay Malkin, Doina Precup, Yoshua Bengio:
Discrete Probabilistic Inference as Control in Multi-path Environments. CoRR abs/2402.10309 (2024) - [i534]Yoshua Bengio, Nikolay Malkin:
Machine learning and information theory concepts towards an AI Mathematician. CoRR abs/2403.04571 (2024) - [i533]Minsu Kim, Sanghyeok Choi, Jiwoo Son, Hyeonah Kim, Jinkyoo Park, Yoshua Bengio:
Ant Colony Sampling with GFlowNets for Combinatorial Optimization. CoRR abs/2403.07041 (2024) - [i532]Nasim Rahaman, Martin Weiss, Manuel Wüthrich, Yoshua Bengio, Li Erran Li, Chris Pal, Bernhard Schölkopf:
Language Models Can Reduce Asymmetry in Information Markets. CoRR abs/2403.14443 (2024) - [i531]Usman Anwar, Abulhair Saparov, Javier Rando, Daniel Paleka, Miles Turpin, Peter Hase, Ekdeep Singh Lubana, Erik Jenner, Stephen Casper, Oliver Sourbut, Benjamin L. Edelman, Zhaowei Zhang, Mario Günther, Anton Korinek, José Hernández-Orallo, Lewis Hammond, Eric J. Bigelow, Alexander Pan, Lauro Langosco, Tomasz Korbak, Heidi Zhang, Ruiqi Zhong, Seán Ó hÉigeartaigh, Gabriel Recchia, Giulio Corsi, Alan Chan, Markus Anderljung, Lilian Edwards, Yoshua Bengio, Danqi Chen, Samuel Albanie, Tegan Maharaj, Jakob N. Foerster, Florian Tramèr, He He, Atoosa Kasirzadeh, Yejin Choi, David Krueger:
Foundational Challenges in Assuring Alignment and Safety of Large Language Models. CoRR abs/2404.09932 (2024) - [i530]Michal Koziarski, Mohammed Abukalam, Vedant Shah, Louis Vaillancourt, Doris Alexandra Schuetz, Moksh Jain, Almer van der Sloot, Mathieu Bourgey, Anne Marinier, Yoshua Bengio:
Towards DNA-Encoded Library Generation with GFlowNets. CoRR abs/2404.10094 (2024) - [i529]Maksym Korablyov, Cheng-Hao Liu, Moksh Jain, Almer M. van der Sloot, Eric Jolicoeur, Edward Ruediger, Andrei Cristian Nica, Emmanuel Bengio, Kostiantyn Lapchevskyi, Daniel St-Cyr, Doris Alexandra Schuetz, Victor Ion Butoi, Jarrid Rector-Brooks, Simon Blackburn, Leo Feng, Hadi Nekoei, Sai Krishna Gottipati, Priyesh Vijayan, Prateek Gupta, Ladislav Rampásek, Sasikanth Avancha, Pierre-Luc Bacon, William L. Hamilton, Brooks Paige, Sanchit Misra, Stanislaw Kamil Jastrzebski, Bharat Kaul, Doina Precup, José Miguel Hernández-Lobato, Marwin H. S. Segler, Michael M. Bronstein, Anne Marinier, Mike Tyers, Yoshua Bengio:
Generative Active Learning for the Search of Small-molecule Protein Binders. CoRR abs/2405.01616 (2024) - [i528]David Dalrymple, Joar Skalse, Yoshua Bengio, Stuart Russell, Max Tegmark, Sanjit Seshia, Steve Omohundro, Christian Szegedy, Ben Goldhaber, Nora Ammann, Alessandro Abate, Joe Halpern, Clark W. Barrett, Ding Zhao, Tan Zhi-Xuan, Jeannette M. Wing, Joshua B. Tenenbaum:
Towards Guaranteed Safe AI: A Framework for Ensuring Robust and Reliable AI Systems. CoRR abs/2405.06624 (2024) - [i527]Aniket Didolkar, Anirudh Goyal, Nan Rosemary Ke, Siyuan Guo, Michal Valko, Timothy P. Lillicrap, Danilo J. Rezende, Yoshua Bengio, Michael Mozer, Sanjeev Arora:
Metacognitive Capabilities of LLMs: An Exploration in Mathematical Problem Solving. CoRR abs/2405.12205 (2024) - [i526]Antoine Bellemare Pépin, François Lespinasse, Philipp Thölke, Yann Harel, Kory W. Mathewson, Jay A. Olson, Yoshua Bengio, Karim Jerbi:
Divergent Creativity in Humans and Large Language Models. CoRR abs/2405.13012 (2024) - [i525]Leo Feng, Frederick Tung, Hossein Hajimirsadeghi, Mohamed Osama Ahmed, Yoshua Bengio, Greg Mori:
Attention as an RNN. CoRR abs/2405.13956 (2024) - [i524]Seanie Lee, Minsu Kim, Lynn Cherif, David Dobre, Juho Lee, Sung Ju Hwang, Kenji Kawaguchi, Gauthier Gidel, Yoshua Bengio, Nikolay Malkin, Moksh Jain:
Learning diverse attacks on large language models for robust red-teaming and safety tuning. CoRR abs/2405.18540 (2024) - [i523]Siddarth Venkatraman, Moksh Jain, Luca Scimeca, Minsu Kim, Marcin Sendera, Mohsin Hasan, Luke Rowe, Sarthak Mittal, Pablo Lemos, Emmanuel Bengio, Alexandre Adam, Jarrid Rector-Brooks, Yoshua Bengio, Glen Berseth, Nikolay Malkin:
Amortizing intractable inference in diffusion models for vision, language, and control. CoRR abs/2405.20971 (2024) - [i522]George Ma, Emmanuel Bengio, Yoshua Bengio, Dinghuai Zhang:
Baking Symmetry into GFlowNets. CoRR abs/2406.05426 (2024) - [i521]Tianyu Zhang, Suyuchen Wang, Lu Li, Ge Zhang, Perouz Taslakian, Sai Rajeswar, Jie Fu, Bang Liu, Yoshua Bengio:
VCR: Visual Caption Restoration. CoRR abs/2406.06462 (2024) - [i520]Lu Li, Tianyu Zhang, Zhiqi Bu, Suyuchen Wang, Huan He, Jie Fu, Yonghui Wu, Jiang Bian, Yong Chen, Yoshua Bengio:
MAP: Low-compute Model Merging with Amortized Pareto Fronts via Quadratic Approximation. CoRR abs/2406.07529 (2024) - [i519]Michal Koziarski, Andrei Rekesh, Dmytro Shevchuk, Almer van der Sloot, Piotr Gainski, Yoshua Bengio, Cheng-Hao Liu, Mike Tyers, Robert A. Batey:
RGFN: Synthesizable Molecular Generation Using GFlowNets. CoRR abs/2406.08506 (2024) - [i518]Anas Krichel, Nikolay Malkin, Salem Lahlou, Yoshua Bengio:
On Generalization for Generative Flow Networks. CoRR abs/2407.03105 (2024) - [i517]Anka Reuel, Ben Bucknall, Stephen Casper, Tim Fist, Lisa Soder, Onni Aarne, Lewis Hammond, Lujain Ibrahim, Alan Chan, Peter Wills, Markus Anderljung, Ben Garfinkel, Lennart Heim, Andrew Trask, Gabriel Mukobi, Rylan Schaeffer, Mauricio Baker, Sara Hooker, Irene Solaiman, Alexandra Sasha Luccioni, Nitarshan Rajkumar, Nicolas Moës, Jeffrey Ladish, Neel Guha, Jessica Newman, Yoshua Bengio, Tobin South, Alex Pentland, Sanmi Koyejo, Mykel J. Kochenderfer, Robert Trager:
Open Problems in Technical AI Governance. CoRR abs/2407.14981 (2024) - [i516]Vedant Shah, Dingli Yu, Kaifeng Lyu, Simon Park, Nan Rosemary Ke, Michael Mozer, Yoshua Bengio, Sanjeev Arora, Anirudh Goyal:
AI-Assisted Generation of Difficult Math Questions. CoRR abs/2407.21009 (2024) - [i515]Stephen Zhewen Lu, Ziqing Lu, Ehsan Hajiramezanali, Tommaso Biancalani, Yoshua Bengio, Gabriele Scalia, Michal Koziarski:
Cell Morphology-Guided Small Molecule Generation with GFlowNets. CoRR abs/2408.05196 (2024) - [i514]Yoshua Bengio, Michael K. Cohen, Nikolay Malkin, Matt MacDermott, Damiano Fornasiere, Pietro Greiner, Younesse Kaddar:
Can a Bayesian Oracle Prevent Harm from an Agent? CoRR abs/2408.05284 (2024) - [i513]Aniket Didolkar, Andrii Zadaianchuk, Anirudh Goyal, Michael C. Mozer, Yoshua Bengio, Georg Martius, Maximilian Seitzer:
Zero-Shot Object-Centric Representation Learning. CoRR abs/2408.09162 (2024) - [i512]Lazar Atanackovic, Xi Zhang, Brandon Amos, Mathieu Blanchette, Leo J. Lee, Yoshua Bengio, Alexander Tong, Kirill Neklyudov:
Meta Flow Matching: Integrating Vector Fields on the Wasserstein Manifold. CoRR abs/2408.14608 (2024) - [i511]Leo Feng, Frederick Tung, Mohamed Osama Ahmed, Yoshua Bengio, Hossein Hajimirsadeghi:
Were RNNs All We Needed? CoRR abs/2410.01201 (2024) - [i510]Minsu Kim, Sanghyeok Choi, Taeyoung Yun, Emmanuel Bengio, Leo Feng, Jarrid Rector-Brooks, Sungsoo Ahn, Jinkyoo Park, Nikolay Malkin, Yoshua Bengio:
Adaptive teachers for amortized samplers. CoRR abs/2410.01432 (2024) - [i509]Jin Hwa Lee, Thomas Jiralerspong, Lei Yu, Yoshua Bengio, Emily Cheng:
Geometric Signatures of Compositionality Across a Language Model's Lifetime. CoRR abs/2410.01444 (2024) - [i508]Seanie Lee, Haebin Seong, Dong Bok Lee, Minki Kang, Xiaoyin Chen, Dominik Wagner, Yoshua Bengio, Juho Lee, Sung Ju Hwang:
HarmAug: Effective Data Augmentation for Knowledge Distillation of Safety Guard Models. CoRR abs/2410.01524 (2024) - [i507]Michael K. Cohen, Marcus Hutter, Yoshua Bengio, Stuart Russell:
RL, but don't do anything I wouldn't do. CoRR abs/2410.06213 (2024) - [i506]Mingde Zhao, Tristan Sylvain, Doina Precup, Yoshua Bengio:
Identifying and Addressing Delusions for Target-Directed Decision-Making. CoRR abs/2410.07096 (2024) - [i505]Jarrid Rector-Brooks, Mohsin Hasan, Zhangzhi Peng, Zachary Quinn, Cheng-Hao Liu, Sarthak Mittal, Nouha Dziri, Michael M. Bronstein, Yoshua Bengio, Pranam Chatterjee, Alexander Tong, Avishek Joey Bose:
Steering Masked Discrete Diffusion Models via Discrete Denoising Posterior Prediction. CoRR abs/2410.08134 (2024) - [i504]Eric Elmoznino, Thomas Jiralerspong, Yoshua Bengio, Guillaume Lajoie:
A Complexity-Based Theory of Compositionality. CoRR abs/2410.14817 (2024) - [i503]Oussama Boussif, Léna Néhale Ezzine, Joseph D. Viviano, Michal Koziarski, Moksh Jain, Nikolay Malkin, Emmanuel Bengio, Rim Assouel, Yoshua Bengio:
Action abstractions for amortized sampling. CoRR abs/2410.15184 (2024) - [i502]Cristian Meo, Akihiro Nakano, Mircea Lica, Aniket Didolkar, Masahiro Suzuki, Anirudh Goyal, Mengmi Zhang, Justin Dauwels, Yutaka Matsuo, Yoshua Bengio:
Object-Centric Temporal Consistency via Conditional Autoregressive Inductive Biases. CoRR abs/2410.15728 (2024) - [i501]Jiarui Lu, Xiaoyin Chen, Stephen Zhewen Lu, Chence Shi, Hongyu Guo, Yoshua Bengio, Jian Tang:
Structure Language Models for Protein Conformation Generation. CoRR abs/2410.18403 (2024) - [i500]Xi Zhang, Yuan Pu, Yuki Kawamura, Andrew Loza, Yoshua Bengio, Dennis L. Shung, Alexander Tong:
Trajectory Flow Matching with Applications to Clinical Time Series Modeling. CoRR abs/2410.21154 (2024) - [i499]Samuel G. B. Johnson, Amir-Hossein Karimi, Yoshua Bengio, Nick Chater, Tobias Gerstenberg, Kate Larson, Sydney Levine, Melanie Mitchell, Iyad Rahwan, Bernhard Schölkopf, Igor Grossmann:
Imagining and building wise machines: The centrality of AI metacognition. CoRR abs/2411.02478 (2024) - [i498]Juan A. Rodriguez, Xiangru Jian, Siba Smarak Panigrahi, Tianyu Zhang, Aarash Feizi, Abhay Puri, Akshay Kalkunte, François Savard, Ahmed Masry, Shravan Nayak, Rabiul Awal, Mahsa Massoud, Amirhossein Abaskohi, Zichao Li, Suyuchen Wang, Pierre-André Noël, Mats Leon Richter, Saverio Vadacchino, Shubbam Agarwal, Sanket Biswas, Sara Shanian, Ying Zhang, Noah Bolger, Kurt MacDonald, Simon Fauvel, Sathwik Tejaswi, Srinivas Sunkara, João Monteiro, Krishnamurthy DJ Dvijotham, Torsten Scholak, Nicolas Chapados, Sepideh Kharagani, Sean Hughes, M. Tamer Özsu, Siva Reddy, Marco Pedersoli, Yoshua Bengio, Christopher Pal, Issam H. Laradji, Spandana Gella, Perouz Taslakian, David Vázquez, Sai Rajeswar:
BigDocs: An Open and Permissively-Licensed Dataset for Training Multimodal Models on Document and Code Tasks. CoRR abs/2412.04626 (2024) - [i497]Yoshua Bengio, Sören Mindermann, Daniel Privitera, Tamay Besiroglu, Rishi Bommasani, Stephen Casper, Yejin Choi, Danielle Goldfarb, Hoda Heidari, Leila Khalatbari, Shayne Longpre, Vasilios Mavroudis, Mantas Mazeika, Kwan Yee Ng, Chinasa T. Okolo, Deborah Raji, Theodora Skeadas, Florian Tramèr, Bayo Adekanmbi, Paul F. Christiano, David Dalrymple, Thomas G. Dietterich, Edward W. Felten, Pascale Fung, Pierre-Olivier Gourinchas, Nick R. Jennings, Andreas Krause, Percy Liang, Teresa Ludermir, Vidushi Marda, Helen Margetts, John A. McDermid, Arvind Narayanan, Alondra Nelson, Alice Oh, Gopal Ramchurn, Stuart Russell, Marietje Schaake, Dawn Song, Alvaro Soto, Lee Tiedrich, Gaël Varoquaux, Andrew Yao, Ya-Qin Zhang:
International Scientific Report on the Safety of Advanced AI (Interim Report). CoRR abs/2412.05282 (2024) - [i496]Zhen Liu, Tim Z. Xiao, Weiyang Liu, Yoshua Bengio, Dinghuai Zhang:
Efficient Diversity-Preserving Diffusion Alignment via Gradient-Informed GFlowNets. CoRR abs/2412.07775 (2024) - 2023
- [j121]David Rolnick, Priya L. Donti, Lynn H. Kaack, Kelly Kochanski, Alexandre Lacoste, Kris Sankaran, Andrew Slavin Ross, Nikola Milojevic-Dupont, Natasha Jaques, Anna Waldman-Brown, Alexandra Sasha Luccioni, Tegan Maharaj, Evan D. Sherwin, S. Karthik Mukkavilli, Konrad P. Kording, Carla P. Gomes, Andrew Y. Ng, Demis Hassabis, John C. Platt, Felix Creutzig, Jennifer T. Chayes, Yoshua Bengio:
Tackling Climate Change with Machine Learning. ACM Comput. Surv. 55(2): 42:1-42:96 (2023) - [j120]Alistair Knott, Dino Pedreschi, Raja Chatila, Tapabrata Chakraborti, Susan Leavy, Ricardo Baeza-Yates, David M. Eyers, Andrew Trotman, Paul D. Teal, Przemyslaw Biecek, Stuart Russell, Yoshua Bengio:
Generative AI models should include detection mechanisms as a condition for public release. Ethics Inf. Technol. 25(4): 55 (2023) - [j119]Vijay Prakash Dwivedi, Chaitanya K. Joshi, Anh Tuan Luu, Thomas Laurent, Yoshua Bengio, Xavier Bresson:
Benchmarking Graph Neural Networks. J. Mach. Learn. Res. 24: 43:1-43:48 (2023) - [j118]Yoshua Bengio, Salem Lahlou, Tristan Deleu, Edward J. Hu, Mo Tiwari, Emmanuel Bengio:
GFlowNet Foundations. J. Mach. Learn. Res. 24: 210:1-210:55 (2023) - [j117]Hanchen Wang, Tianfan Fu, Yuanqi Du, Wenhao Gao, Kexin Huang, Ziming Liu, Payal Chandak, Shengchao Liu, Peter Van Katwyk, Andreea Deac, Anima Anandkumar, Karianne Bergen, Carla P. Gomes, Shirley Ho, Pushmeet Kohli, Joan Lasenby, Jure Leskovec, Tie-Yan Liu, Arjun Manrai, Debora S. Marks, Bharath Ramsundar, Le Song, Jimeng Sun, Jian Tang, Petar Velickovic, Max Welling, Linfeng Zhang, Connor W. Coley, Yoshua Bengio, Marinka Zitnik:
Scientific discovery in the age of artificial intelligence. Nat. 620(7972): 47-60 (2023) - [j116]Nan Rosemary Ke, Olexa Bilaniuk, Anirudh Goyal, Stefan Bauer, Hugo Larochelle, Bernhard Schölkopf, Michael Curtis Mozer, Christopher Pal, Yoshua Bengio:
Neural Causal Structure Discovery from Interventions. Trans. Mach. Learn. Res. 2023 (2023) - [j115]Salem Lahlou, Moksh Jain, Hadi Nekoei, Victor Butoi, Paul Bertin, Jarrid Rector-Brooks, Maksym Korablyov, Yoshua Bengio:
DEUP: Direct Epistemic Uncertainty Prediction. Trans. Mach. Learn. Res. 2023 (2023) - [c438]Ramnath Kumar, Tristan Deleu, Yoshua Bengio:
The Effect of Diversity in Meta-Learning. AAAI 2023: 8396-8404 - [c437]Dianbo Liu, Alex Lamb, Xu Ji, Pascal Tikeng Notsawo Jr., Michael Mozer, Yoshua Bengio, Kenji Kawaguchi:
Adaptive Discrete Communication Bottlenecks with Dynamic Vector Quantization for Heterogeneous Representational Coarseness. AAAI 2023: 8825-8833 - [c436]Edoardo Maria Ponti, Alessandro Sordoni, Yoshua Bengio, Siva Reddy:
Combining Parameter-efficient Modules for Task-level Generalisation. EACL 2023: 687-702 - [c435]Leo Feng, Hossein Hajimirsadeghi, Yoshua Bengio, Mohamed Osama Ahmed:
Latent Bottlenecked Attentive Neural Processes. ICLR 2023 - [c434]Dianbo Liu, Vedant Shah, Oussama Boussif, Cristian Meo, Anirudh Goyal, Tianmin Shu, Michael Curtis Mozer, Nicolas Heess, Yoshua Bengio:
Stateful Active Facilitator: Coordination and Environmental Heterogeneity in Cooperative Multi-Agent Reinforcement Learning. ICLR 2023 - [c433]Nikolay Malkin, Salem Lahlou, Tristan Deleu, Xu Ji, Edward J. Hu, Katie Everett, Dinghuai Zhang, Yoshua Bengio:
GFlowNets and variational inference. ICLR 2023 - [c432]Ling Pan, Dinghuai Zhang, Aaron C. Courville, Longbo Huang, Yoshua Bengio:
Generative Augmented Flow Networks. ICLR 2023 - [c431]Jiaye Teng, Chuan Wen, Dinghuai Zhang, Yoshua Bengio, Yang Gao, Yang Yuan:
Predictive Inference with Feature Conformal Prediction. ICLR 2023 - [c430]Dinghuai Zhang, Aaron C. Courville, Yoshua Bengio, Qinqing Zheng, Amy Zhang, Ricky T. Q. Chen:
Latent State Marginalization as a Low-cost Approach for Improving Exploration. ICLR 2023 - [c429]Ruixiang Zhang, Tong Che, Boris Ivanovic, Renhao Wang, Marco Pavone, Yoshua Bengio, Liam Paull:
Robust and Controllable Object-Centric Learning through Energy-based Models. ICLR 2023 - [c428]Kartik Ahuja, Divyat Mahajan, Yixin Wang, Yoshua Bengio:
Interventional Causal Representation Learning. ICML 2023: 372-407 - [c427]Alexandre Duval, Victor Schmidt, Alex Hernández-García, Santiago Miret, Fragkiskos D. Malliaros, Yoshua Bengio, David Rolnick:
FAENet: Frame Averaging Equivariant GNN for Materials Modeling. ICML 2023: 9013-9033 - [c426]Edward J. Hu, Nikolay Malkin, Moksh Jain, Katie E. Everett, Alexandros Graikos, Yoshua Bengio:
GFlowNet-EM for Learning Compositional Latent Variable Models. ICML 2023: 13528-13549 - [c425]Moksh Jain, Sharath Chandra Raparthy, Alex Hernández-García, Jarrid Rector-Brooks, Yoshua Bengio, Santiago Miret, Emmanuel Bengio:
Multi-Objective GFlowNets. ICML 2023: 14631-14653 - [c424]Sékou-Oumar Kaba, Arnab Kumar Mondal, Yan Zhang, Yoshua Bengio, Siamak Ravanbakhsh:
Equivariance with Learned Canonicalization Functions. ICML 2023: 15546-15566 - [c423]Sébastien Lachapelle, Tristan Deleu, Divyat Mahajan, Ioannis Mitliagkas, Yoshua Bengio, Simon Lacoste-Julien, Quentin Bertrand:
Synergies between Disentanglement and Sparsity: Generalization and Identifiability in Multi-Task Learning. ICML 2023: 18171-18206 - [c422]Salem Lahlou, Tristan Deleu, Pablo Lemos, Dinghuai Zhang, Alexandra Volokhova, Alex Hernández-García, Léna Néhale Ezzine, Yoshua Bengio, Nikolay Malkin:
A theory of continuous generative flow networks. ICML 2023: 18269-18300 - [c421]Dianbo Liu, Moksh Jain, Bonaventure F. P. Dossou, Qianli Shen, Salem Lahlou, Anirudh Goyal, Nikolay Malkin, Chris Chinenye Emezue, Dinghuai Zhang, Nadhir Hassen, Xu Ji, Kenji Kawaguchi, Yoshua Bengio:
GFlowOut: Dropout with Generative Flow Networks. ICML 2023: 21715-21729 - [c420]Kanika Madan, Jarrid Rector-Brooks, Maksym Korablyov, Emmanuel Bengio, Moksh Jain, Andrei Cristian Nica, Tom Bosc, Yoshua Bengio, Nikolay Malkin:
Learning GFlowNets From Partial Episodes For Improved Convergence And Stability. ICML 2023: 23467-23483 - [c419]Ling Pan, Nikolay Malkin, Dinghuai Zhang, Yoshua Bengio:
Better Training of GFlowNets with Local Credit and Incomplete Trajectories. ICML 2023: 26878-26890 - [c418]Michael Poli, Stefano Massaroli, Eric Nguyen, Daniel Y. Fu, Tri Dao, Stephen Baccus, Yoshua Bengio, Stefano Ermon, Christopher Ré:
Hyena Hierarchy: Towards Larger Convolutional Language Models. ICML 2023: 28043-28078 - [c417]Frederik Träuble, Anirudh Goyal, Nasim Rahaman, Michael Curtis Mozer, Kenji Kawaguchi, Yoshua Bengio, Bernhard Schölkopf:
Discrete Key-Value Bottleneck. ICML 2023: 34431-34455 - [c416]Chen Sun, Wannan Yang, Thomas Jiralerspong, Dane Malenfant, Benjamin Alsbury-Nealy, Yoshua Bengio, Blake A. Richards:
Contrastive Retrospection: honing in on critical steps for rapid learning and generalization in RL. NeurIPS 2023 - [c415]Lazar Atanackovic, Alexander Tong, Bo Wang, Leo J. Lee, Yoshua Bengio, Jason S. Hartford:
DynGFN: Towards Bayesian Inference of Gene Regulatory Networks with GFlowNets. NeurIPS 2023 - [c414]Oussama Boussif, Ghait Boukachab, Dan Assouline, Stefano Massaroli, Tianle Yuan, Loubna Benabbou, Yoshua Bengio:
Improving *day-ahead* Solar Irradiance Time Series Forecasting by Leveraging Spatio-Temporal Context. NeurIPS 2023 - [c413]Tristan Deleu, Mizu Nishikawa-Toomey, Jithendaraa Subramanian, Nikolay Malkin, Laurent Charlin, Yoshua Bengio:
Joint Bayesian Inference of Graphical Structure and Parameters with a Single Generative Flow Network. NeurIPS 2023 - [c412]Alexandre Lacoste, Nils Lehmann, Pau Rodríguez, Evan D. Sherwin, Hannah Kerner, Björn Lütjens, Jeremy Irvin, David Dao, Hamed Alemohammad, Alexandre Drouin, Mehmet Gunturkun, Gabriel Huang, David Vázquez, Dava Newman, Yoshua Bengio, Stefano Ermon, Xiaoxiang Zhu:
GEO-Bench: Toward Foundation Models for Earth Monitoring. NeurIPS 2023 - [c411]Stefano Massaroli, Michael Poli, Daniel Y. Fu, Hermann Kumbong, Rom N. Parnichkun, David W. Romero, Aman Timalsina, Quinn McIntyre, Beidi Chen, Atri Rudra, Ce Zhang, Christopher Ré, Stefano Ermon, Yoshua Bengio:
Laughing Hyena Distillery: Extracting Compact Recurrences From Convolutions. NeurIPS 2023 - [c410]Trang Nguyen, Amin Mansouri, Kanika Madan, Khuong Nguyen, Kartik Ahuja, Dianbo Liu, Yoshua Bengio:
Reusable Slotwise Mechanisms. NeurIPS 2023 - [c409]Eric Nguyen, Michael Poli, Marjan Faizi, Armin W. Thomas, Michael Wornow, Callum Birch-Sykes, Stefano Massaroli, Aman Patel, Clayton M. Rabideau, Yoshua Bengio, Stefano Ermon, Christopher Ré, Stephen Baccus:
HyenaDNA: Long-Range Genomic Sequence Modeling at Single Nucleotide Resolution. NeurIPS 2023 - [c408]Mélisande Teng, Amna Elmustafa, Benjamin Akera, Yoshua Bengio, Hager Radi Abdelwahed, Hugo Larochelle, David Rolnick:
SatBird: a Dataset for Bird Species Distribution Modeling using Remote Sensing and Citizen Science Data. NeurIPS 2023 - [c407]Dinghuai Zhang, Hanjun Dai, Nikolay Malkin, Aaron C. Courville, Yoshua Bengio, Ling Pan:
Let the Flows Tell: Solving Graph Combinatorial Problems with GFlowNets. NeurIPS 2023 - [c406]Ling Pan, Dinghuai Zhang, Moksh Jain, Longbo Huang, Yoshua Bengio:
Stochastic Generative Flow Networks. UAI 2023: 1628-1638 - [c405]Yingtian Zou, Vikas Verma, Sarthak Mittal, Wai Hoh Tang, Hieu Pham, Juho Kannala, Yoshua Bengio, Arno Solin, Kenji Kawaguchi:
MixupE: Understanding and improving Mixup from directional derivative perspective. UAI 2023: 2597-2607 - [i495]Xu Tan, Tao Qin, Jiang Bian, Tie-Yan Liu, Yoshua Bengio:
Regeneration Learning: A Learning Paradigm for Data Generation. CoRR abs/2301.08846 (2023) - [i494]Sumukh K. Aithal, Anirudh Goyal, Alex Lamb, Yoshua Bengio, Michael Mozer:
Leveraging the Third Dimension in Contrastive Learning. CoRR abs/2301.11790 (2023) - [i493]Salem Lahlou, Tristan Deleu, Pablo Lemos, Dinghuai Zhang, Alexandra Volokhova, Alex Hernández-García, Léna Néhale Ezzine, Yoshua Bengio, Nikolay Malkin:
A theory of continuous generative flow networks. CoRR abs/2301.12594 (2023) - [i492]Alexander Tong, Nikolay Malkin, Guillaume Huguet, Yanlei Zhang, Jarrid Rector-Brooks, Kilian Fatras, Guy Wolf, Yoshua Bengio:
Conditional Flow Matching: Simulation-Free Dynamic Optimal Transport. CoRR abs/2302.00482 (2023) - [i491]Moksh Jain, Tristan Deleu, Jason S. Hartford, Cheng-Hao Liu, Alex Hernández-García, Yoshua Bengio:
GFlowNets for AI-Driven Scientific Discovery. CoRR abs/2302.00615 (2023) - [i490]Ling Pan, Nikolay Malkin, Dinghuai Zhang, Yoshua Bengio:
Better Training of GFlowNets with Local Credit and Incomplete Trajectories. CoRR abs/2302.01687 (2023) - [i489]Lazar Atanackovic, Alexander Tong, Jason S. Hartford, Leo J. Lee, Bo Wang, Yoshua Bengio:
DynGFN: Bayesian Dynamic Causal Discovery using Generative Flow Networks. CoRR abs/2302.04178 (2023) - [i488]Dinghuai Zhang, Ling Pan, Ricky T. Q. Chen, Aaron C. Courville, Yoshua Bengio:
Distributional GFlowNets with Quantile Flows. CoRR abs/2302.05793 (2023) - [i487]Xu Ji, Eric Elmoznino, George Deane, Axel Constant, Guillaume Dumas, Guillaume Lajoie, Jonathan Simon, Yoshua Bengio:
Sources of Richness and Ineffability for Phenomenally Conscious States. CoRR abs/2302.06403 (2023) - [i486]Edward J. Hu, Nikolay Malkin, Moksh Jain, Katie Everett, Alexandros Graikos, Yoshua Bengio:
GFlowNet-EM for learning compositional latent variable models. CoRR abs/2302.06576 (2023) - [i485]Ling Pan, Dinghuai Zhang, Moksh Jain, Longbo Huang, Yoshua Bengio:
Stochastic Generative Flow Networks. CoRR abs/2302.09465 (2023) - [i484]Trang Nguyen, Amin Mansouri, Kanika Madan, Khuong Nguyen, Kartik Ahuja, Dianbo Liu, Yoshua Bengio:
Reusable Slotwise Mechanisms. CoRR abs/2302.10503 (2023) - [i483]Michael Poli, Stefano Massaroli, Eric Nguyen, Daniel Y. Fu, Tri Dao, Stephen Baccus, Yoshua Bengio, Stefano Ermon, Christopher Ré:
Hyena Hierarchy: Towards Larger Convolutional Language Models. CoRR abs/2302.10866 (2023) - [i482]Alexandre Duval, Victor Schmidt, Alex Hernández-García, Santiago Miret, Fragkiskos D. Malliaros, Yoshua Bengio, David Rolnick:
FAENet: Frame Averaging Equivariant GNN for Materials Modeling. CoRR abs/2305.05577 (2023) - [i481]Leo Feng, Frederick Tung, Hossein Hajimirsadeghi, Yoshua Bengio, Mohamed Osama Ahmed:
Constant Memory Attentive Neural Processes. CoRR abs/2305.14567 (2023) - [i480]Toby Shevlane, Sebastian Farquhar, Ben Garfinkel, Mary Phuong, Jess Whittlestone, Jade Leung, Daniel Kokotajlo, Nahema Marchal, Markus Anderljung, Noam Kolt, Lewis Ho, Divya Siddarth, Shahar Avin, Will Hawkins, Been Kim, Iason Gabriel, Vijay Bolina, Jack Clark, Yoshua Bengio, Paul F. Christiano, Allan Dafoe:
Model evaluation for extreme risks. CoRR abs/2305.15324 (2023) - [i479]Dinghuai Zhang, Hanjun Dai, Nikolay Malkin, Aaron C. Courville, Yoshua Bengio, Ling Pan:
Let the Flows Tell: Solving Graph Combinatorial Optimization Problems with GFlowNets. CoRR abs/2305.17010 (2023) - [i478]Dianbo Liu, Samuele Bolotta, He Zhu, Yoshua Bengio, Guillaume Dumas:
Attention Schema in Neural Agents. CoRR abs/2305.17375 (2023) - [i477]Tristan Deleu, Mizu Nishikawa-Toomey, Jithendaraa Subramanian, Nikolay Malkin, Laurent Charlin, Yoshua Bengio:
Joint Bayesian Inference of Graphical Structure and Parameters with a Single Generative Flow Network. CoRR abs/2305.19366 (2023) - [i476]Ayush Chakravarthy, Trang Nguyen, Anirudh Goyal, Yoshua Bengio, Michael C. Mozer:
Spotlight Attention: Robust Object-Centric Learning With a Spatial Locality Prior. CoRR abs/2305.19550 (2023) - [i475]Oussama Boussif, Ghait Boukachab, Dan Assouline, Stefano Massaroli, Tianle Yuan, Loubna Benabbou, Yoshua Bengio:
What if We Enrich day-ahead Solar Irradiance Time Series Forecasting with Spatio-Temporal Context? CoRR abs/2306.01112 (2023) - [i474]Aniket Didolkar, Anirudh Goyal, Yoshua Bengio:
Cycle Consistency Driven Object Discovery. CoRR abs/2306.02204 (2023) - [i473]Alexandre Lacoste, Nils Lehmann, Pau Rodríguez, Evan David Sherwin, Hannah Kerner, Björn Lütjens, Jeremy Andrew Irvin, David Dao, Hamed Alemohammad, Alexandre Drouin, Mehmet Gunturkun, Gabriel Huang, David Vázquez, Dava Newman, Yoshua Bengio, Stefano Ermon, Xiao Xiang Zhu:
GEO-Bench: Toward Foundation Models for Earth Monitoring. CoRR abs/2306.03831 (2023) - [i472]Alex Hernández-García, Nikita Saxena, Moksh Jain, Cheng-Hao Liu, Yoshua Bengio:
Multi-Fidelity Active Learning with GFlowNets. CoRR abs/2306.11715 (2023) - [i471]Leo Feng, Frederick Tung, Hossein Hajimirsadeghi, Yoshua Bengio, Mohamed Osama Ahmed:
Constant Memory Attention Block. CoRR abs/2306.12599 (2023) - [i470]Shreshth A. Malik, Salem Lahlou, Andrew Jesson, Moksh Jain, Nikolay Malkin, Tristan Deleu, Yoshua Bengio, Yarin Gal:
BatchGFN: Generative Flow Networks for Batch Active Learning. CoRR abs/2306.15058 (2023) - [i469]Eric Nguyen, Michael Poli, Marjan Faizi, Armin W. Thomas, Callum Birch-Sykes, Michael Wornow, Aman Patel, Clayton M. Rabideau, Stefano Massaroli, Yoshua Bengio, Stefano Ermon, Stephen A. Baccus, Christopher Ré:
HyenaDNA: Long-Range Genomic Sequence Modeling at Single Nucleotide Resolution. CoRR abs/2306.15794 (2023) - [i468]Jarrid Rector-Brooks, Kanika Madan, Moksh Jain, Maksym Korablyov, Cheng-Hao Liu, Sarath Chandar, Nikolay Malkin, Yoshua Bengio:
Thompson sampling for improved exploration in GFlowNets. CoRR abs/2306.17693 (2023) - [i467]Tristan Deleu, Yoshua Bengio:
Generative Flow Networks: a Markov Chain Perspective. CoRR abs/2307.01422 (2023) - [i466]Alexander Tong, Nikolay Malkin, Kilian Fatras, Lazar Atanackovic, Yanlei Zhang, Guillaume Huguet, Guy Wolf, Yoshua Bengio:
Simulation-free Schrödinger bridges via score and flow matching. CoRR abs/2307.03672 (2023) - [i465]Lewis Ho, Joslyn Barnhart, Robert Trager, Yoshua Bengio, Miles Brundage, Allison Carnegie, Rumman Chowdhury, Allan Dafoe, Gillian K. Hadfield, Margaret Levi, Duncan Snidal:
International Institutions for Advanced AI. CoRR abs/2307.04699 (2023) - [i464]Chris Chinenye Emezue, Alexandre Drouin, Tristan Deleu, Stefan Bauer, Yoshua Bengio:
Benchmarking Bayesian Causal Discovery Methods for Downstream Treatment Effect Estimation. CoRR abs/2307.04988 (2023) - [i463]Yoshua Bengio, Prateek Gupta, Lu Li, Soham Phade, Sunil Srinivasa, Andrew Williams, Tianyu Zhang, Yang Zhang, Stephan Zheng:
AI For Global Climate Cooperation 2023 Competition Proceedings. CoRR abs/2307.06951 (2023) - [i462]Patrick Butlin, Robert Long, Eric Elmoznino, Yoshua Bengio, Jonathan Birch, Axel Constant, George Deane, Stephen M. Fleming, Chris Frith, Xu Ji, Ryota Kanai, Colin Klein, Grace Lindsay, Matthias Michel, Liad Mudrik, Megan A. K. Peters, Eric Schwitzgebel, Jonathan Simon, Rufin VanRullen:
Consciousness in Artificial Intelligence: Insights from the Science of Consciousness. CoRR abs/2308.08708 (2023) - [i461]Leo Feng, Frederick Tung, Hossein Hajimirsadeghi, Yoshua Bengio, Mohamed Osama Ahmed:
Tree Cross Attention. CoRR abs/2309.17388 (2023) - [i460]Mingde Zhao, Safa Alver, Harm van Seijen, Romain Laroche, Doina Precup, Yoshua Bengio:
Combining Spatial and Temporal Abstraction in Planning for Better Generalization. CoRR abs/2310.00229 (2023) - [i459]Andrew Nam, Eric Elmoznino, Nikolay Malkin, Chen Sun, Yoshua Bengio, Guillaume Lajoie:
Discrete, compositional, and symbolic representations through attractor dynamics. CoRR abs/2310.01807 (2023) - [i458]Luca Scimeca, Alexander Rubinstein, Armand Mihai Nicolicioiu, Damien Teney, Yoshua Bengio:
Leveraging Diffusion Disentangled Representations to Mitigate Shortcuts in Underspecified Visual Tasks. CoRR abs/2310.02230 (2023) - [i457]Jean-Pierre R. Falet, Hae Beom Lee, Nikolay Malkin, Chen Sun, Dragos Secrieru, Dinghuai Zhang, Guillaume Lajoie, Yoshua Bengio:
Delta-AI: Local objectives for amortized inference in sparse graphical models. CoRR abs/2310.02423 (2023) - [i456]Dinghuai Zhang, Ricky Tian Qi Chen, Cheng-Hao Liu, Aaron C. Courville, Yoshua Bengio:
Diffusion Generative Flow Samplers: Improving learning signals through partial trajectory optimization. CoRR abs/2310.02679 (2023) - [i455]Minsu Kim, Taeyoung Yun, Emmanuel Bengio, Dinghuai Zhang, Yoshua Bengio, Sungsoo Ahn, Jinkyoo Park:
Local Search GFlowNets. CoRR abs/2310.02710 (2023) - [i454]Marco Jiralerspong, Bilun Sun, Danilo Vucetic, Tianyu Zhang, Yoshua Bengio, Gauthier Gidel, Nikolay Malkin:
Expected flow networks in stochastic environments and two-player zero-sum games. CoRR abs/2310.02779 (2023) - [i453]Minsu Kim, Joohwan Ko, Dinghuai Zhang, Ling Pan, Taeyoung Yun, Woochang Kim, Jinkyoo Park, Yoshua Bengio:
Learning to Scale Logits for Temperature-Conditional GFlowNets. CoRR abs/2310.02823 (2023) - [i452]Ling Pan, Moksh Jain, Kanika Madan, Yoshua Bengio:
Pre-Training and Fine-Tuning Generative Flow Networks. CoRR abs/2310.03419 (2023) - [i451]Trang Nguyen, Alexander Tong, Kanika Madan, Yoshua Bengio, Dianbo Liu:
Causal Inference in Gene Regulatory Networks with GFlowNet: Towards Scalability in Large Systems. CoRR abs/2310.03579 (2023) - [i450]Edward J. Hu, Moksh Jain, Eric Elmoznino, Younesse Kaddar, Guillaume Lajoie, Yoshua Bengio, Nikolay Malkin:
Amortizing intractable inference in large language models. CoRR abs/2310.04363 (2023) - [i449]Alex Hernández-García, Alexandre Duval, Alexandra Volokhova, Yoshua Bengio, Divya Sharma, Pierre Luc Carrier, Michal Koziarski, Victor Schmidt:
Crystal-GFN: sampling crystals with desirable properties and constraints. CoRR abs/2310.04925 (2023) - [i448]Alvaro Carbonero, Alexandre Duval, Victor Schmidt, Santiago Miret, Alex Hernández-García, Yoshua Bengio, David Rolnick:
On the importance of catalyst-adsorbate 3D interactions for relaxed energy predictions. CoRR abs/2310.06682 (2023) - [i447]Charles C. Onu, Samantha Latremouille, Arsenii Gorin, Junhao Wang, Uchenna Ekwochi, Peter O. Ubuane, Omolara A. Kehinde, Muhammad A. Salisu, Datonye Briggs, Yoshua Bengio, Doina Precup:
A cry for help: Early detection of brain injury in newborns. CoRR abs/2310.08338 (2023) - [i446]Mingyang Zhou, Zichao Yan, Elliot Layne, Nikolay Malkin, Dinghuai Zhang, Moksh Jain, Mathieu Blanchette, Yoshua Bengio:
PhyloGFN: Phylogenetic inference with generative flow networks. CoRR abs/2310.08774 (2023) - [i445]Alexandra Volokhova, Michal Koziarski, Alex Hernández-García, Cheng-Hao Liu, Santiago Miret, Pablo Lemos, Luca A. Thiede, Zichao Yan, Alán Aspuru-Guzik, Yoshua Bengio:
Towards equilibrium molecular conformation generation with GFlowNets. CoRR abs/2310.14782 (2023) - [i444]Alejandro Tejada-Lapuerta, Paul Bertin, Stefan Bauer, Hananeh Aliee, Yoshua Bengio, Fabian J. Theis:
Causal machine learning for single-cell genomics. CoRR abs/2310.14935 (2023) - [i443]Yoshua Bengio, Geoffrey E. Hinton, Andrew Yao, Dawn Song, Pieter Abbeel, Yuval Noah Harari, Ya-Qin Zhang, Lan Xue, Shai Shalev-Shwartz, Gillian K. Hadfield, Jeff Clune, Tegan Maharaj, Frank Hutter, Atilim Günes Baydin, Sheila A. McIlraith, Qiqi Gao, Ashwin Acharya, David Krueger, Anca D. Dragan, Philip H. S. Torr, Stuart Russell, Daniel Kahneman, Jan Brauner, Sören Mindermann:
Managing AI Risks in an Era of Rapid Progress. CoRR abs/2310.17688 (2023) - [i442]Stefano Massaroli, Michael Poli, Daniel Y. Fu, Hermann Kumbong, Rom N. Parnichkun, Aman Timalsina, David W. Romero, Quinn McIntyre, Beidi Chen, Atri Rudra, Ce Zhang, Christopher Ré, Stefano Ermon, Yoshua Bengio:
Laughing Hyena Distillery: Extracting Compact Recurrences From Convolutions. CoRR abs/2310.18780 (2023) - [i441]Rim Assouel, Pau Rodríguez, Perouz Taslakian, David Vázquez, Yoshua Bengio:
OC-NMN: Object-centric Compositional Neural Module Network for Generative Visual Analogical Reasoning. CoRR abs/2310.18807 (2023) - [i440]Amin Mansouri, Jason S. Hartford, Yan Zhang, Yoshua Bengio:
Object-centric architectures enable efficient causal representation learning. CoRR abs/2310.19054 (2023) - [i439]Mélisande Teng, Amna Elmustafa, Benjamin Akera, Yoshua Bengio, Hager Radi Abdelwahed, Hugo Larochelle, David Rolnick:
SatBird: Bird Species Distribution Modeling with Remote Sensing and Citizen Science Data. CoRR abs/2311.00936 (2023) - [i438]Vedant Shah, Frederik Träuble, Ashish Malik, Hugo Larochelle, Michael Mozer, Sanjeev Arora, Yoshua Bengio, Anirudh Goyal:
Unlearning via Sparse Representations. CoRR abs/2311.15268 (2023) - [i437]Luca Scimeca, Alexander Rubinstein, Damien Teney, Seong Joon Oh, Armand Mihai Nicolicioiu, Yoshua Bengio:
Shortcut Bias Mitigation via Ensemble Diversity Using Diffusion Probabilistic Models. CoRR abs/2311.16176 (2023) - [i436]Pablo Lemos, Nikolay Malkin, Will Handley, Yoshua Bengio, Yashar Hezaveh, Laurence Perreault Levasseur:
Improving Gradient-guided Nested Sampling for Posterior Inference. CoRR abs/2312.03911 (2023) - [i435]Alexandre Duval, Simon V. Mathis, Chaitanya K. Joshi, Victor Schmidt, Santiago Miret, Fragkiskos D. Malliaros, Taco Cohen, Pietro Lio, Yoshua Bengio, Michael M. Bronstein:
A Hitchhiker's Guide to Geometric GNNs for 3D Atomic Systems. CoRR abs/2312.07511 (2023) - 2022
- [j114]Eric Larsen, Sébastien Lachapelle, Yoshua Bengio, Emma Frejinger, Simon Lacoste-Julien, Andrea Lodi:
Predicting Tactical Solutions to Operational Planning Problems Under Imperfect Information. INFORMS J. Comput. 34(1): 227-242 (2022) - [j113]Cheng-Hao Liu, Maksym Korablyov, Stanislaw Jastrzebski, Pawel Wlodarczyk-Pruszynski, Yoshua Bengio, Marwin H. S. Segler:
RetroGNN: Fast Estimation of Synthesizability for Virtual Screening and De Novo Design by Learning from Slow Retrosynthesis Software. J. Chem. Inf. Model. 62(10): 2293-2300 (2022) - [j112]Vikas Verma, Kenji Kawaguchi, Alex Lamb, Juho Kannala, Arno Solin, Yoshua Bengio, David Lopez-Paz:
Interpolation consistency training for semi-supervised learning. Neural Networks 145: 90-106 (2022) - [j111]Alex Lamb, Vikas Verma, Kenji Kawaguchi, Alexander Matyasko, Savya Khosla, Juho Kannala, Yoshua Bengio:
Interpolated Adversarial Training: Achieving robust neural networks without sacrificing too much accuracy. Neural Networks 154: 218-233 (2022) - [j110]Prateek Gupta, Elias Boutros Khalil, Didier Chételat, Maxime Gasse, Andrea Lodi, Yoshua Bengio, M. Pawan Kumar:
Lookback for Learning to Branch. Trans. Mach. Learn. Res. 2022 (2022) - [j109]Qicheng Lao, Xiang Jiang, Mohammad Havaei, Yoshua Bengio:
A Two-Stream Continual Learning System With Variational Domain-Agnostic Feature Replay. IEEE Trans. Neural Networks Learn. Syst. 33(9): 4466-4478 (2022) - [c404]Tianyi Zhang, Shirui Zhang, Ziwei Chen, Yoshua Bengio, Dianbo Liu:
PMFL: Partial Meta-Federated Learning for heterogeneous tasks and its applications on real-world medical records. IEEE Big Data 2022: 4453-4462 - [c403]Rim Assouel, Lluís Castrejón, Aaron C. Courville, Nicolas Ballas, Yoshua Bengio:
VIM: Variational Independent Modules for Video Prediction. CLeaR 2022: 70-89 - [c402]Kartik Ahuja, Jason S. Hartford, Yoshua Bengio:
Properties from mechanisms: an equivariance perspective on identifiable representation learning. ICLR 2022 - [c401]Tristan Deleu, David Kanaa, Leo Feng, Giancarlo Kerg, Yoshua Bengio, Guillaume Lajoie, Pierre-Luc Bacon:
Continuous-Time Meta-Learning with Forward Mode Differentiation. ICLR 2022 - [c400]Vijay Prakash Dwivedi, Anh Tuan Luu, Thomas Laurent, Yoshua Bengio, Xavier Bresson:
Graph Neural Networks with Learnable Structural and Positional Representations. ICLR 2022 - [c399]Anirudh Goyal, Aniket Rajiv Didolkar, Alex Lamb, Kartikeya Badola, Nan Rosemary Ke, Nasim Rahaman, Jonathan Binas, Charles Blundell, Michael Curtis Mozer, Yoshua Bengio:
Coordination Among Neural Modules Through a Shared Global Workspace. ICLR 2022 - [c398]Sarthak Mittal, Sharath Chandra Raparthy, Irina Rish, Yoshua Bengio, Guillaume Lajoie:
Compositional Attention: Disentangling Search and Retrieval. ICLR 2022 - [c397]Max Morrison, Rithesh Kumar, Kundan Kumar, Prem Seetharaman, Aaron C. Courville, Yoshua Bengio:
Chunked Autoregressive GAN for Conditional Waveform Synthesis. ICLR 2022 - [c396]Victor Schmidt, Alexandra Luccioni, Mélisande Teng, Tianyu Zhang, Alexia Reynaud, Sunand Raghupathi, Gautier Cosne, Adrien Juraver, Vahe Vardanyan, Alex Hernández-García, Yoshua Bengio:
ClimateGAN: Raising Climate Change Awareness by Generating Images of Floods. ICLR 2022 - [c395]Dinghuai Zhang, Jie Fu, Yoshua Bengio, Aaron C. Courville:
Unifying Likelihood-free Inference with Black-box Optimization and Beyond. ICLR 2022 - [c394]Maxence Ernoult, Fabrice Normandin, Abhinav Moudgil, Sean Spinney, Eugene Belilovsky, Irina Rish, Blake A. Richards, Yoshua Bengio:
Towards Scaling Difference Target Propagation by Learning Backprop Targets. ICML 2022: 5968-5987 - [c393]Moksh Jain, Emmanuel Bengio, Alex Hernández-García, Jarrid Rector-Brooks, Bonaventure F. P. Dossou, Chanakya Ajit Ekbote, Jie Fu, Tianyu Zhang, Michael Kilgour, Dinghuai Zhang, Lena Simine, Payel Das, Yoshua Bengio:
Biological Sequence Design with GFlowNets. ICML 2022: 9786-9801 - [c392]Mohammad Pezeshki, Amartya Mitra, Yoshua Bengio, Guillaume Lajoie:
Multi-scale Feature Learning Dynamics: Insights for Double Descent. ICML 2022: 17669-17690 - [c391]Dinghuai Zhang, Nikolay Malkin, Zhen Liu, Alexandra Volokhova, Aaron C. Courville, Yoshua Bengio:
Generative Flow Networks for Discrete Probabilistic Modeling. ICML 2022: 26412-26428 - [c390]Dinghuai Zhang, Hongyang Zhang, Aaron C. Courville, Yoshua Bengio, Pradeep Ravikumar, Arun Sai Suggala:
Building Robust Ensembles via Margin Boosting. ICML 2022: 26669-26692 - [c389]Kartik Ahuja, Jason S. Hartford, Yoshua Bengio:
Weakly Supervised Representation Learning with Sparse Perturbations. NeurIPS 2022 - [c388]Oussama Boussif, Yoshua Bengio, Loubna Benabbou, Dan Assouline:
MAgNet: Mesh Agnostic Neural PDE Solver. NeurIPS 2022 - [c387]Aniket Didolkar, Kshitij Gupta, Anirudh Goyal, Nitesh B. Gundavarapu, Alex Lamb, Nan Rosemary Ke, Yoshua Bengio:
Temporal Latent Bottleneck: Synthesis of Fast and Slow Processing Mechanisms in Sequence Learning. NeurIPS 2022 - [c386]Jose Gallego-Posada, Juan Ramirez, Akram Erraqabi, Yoshua Bengio, Simon Lacoste-Julien:
Controlled Sparsity via Constrained Optimization or: How I Learned to Stop Tuning Penalties and Love Constraints. NeurIPS 2022 - [c385]Riashat Islam, Hongyu Zang, Anirudh Goyal, Alex Lamb, Kenji Kawaguchi, Xin Li, Romain Laroche, Yoshua Bengio, Remi Tachet des Combes:
Discrete Compositional Representations as an Abstraction for Goal Conditioned Reinforcement Learning. NeurIPS 2022 - [c384]Nikolay Malkin, Moksh Jain, Emmanuel Bengio, Chen Sun, Yoshua Bengio:
Trajectory balance: Improved credit assignment in GFlowNets. NeurIPS 2022 - [c383]Sarthak Mittal, Yoshua Bengio, Guillaume Lajoie:
Is a Modular Architecture Enough? NeurIPS 2022 - [c382]Martin Weiss, Nasim Rahaman, Francesco Locatello, Chris Pal, Yoshua Bengio, Bernhard Schölkopf, Li Erran Li, Nicolas Ballas:
Neural Attentive Circuits. NeurIPS 2022 - [c381]Tristan Deleu, António Góis, Chris Emezue, Mansi Rankawat, Simon Lacoste-Julien, Stefan Bauer, Yoshua Bengio:
Bayesian structure learning with generative flow networks. UAI 2022: 518-528 - [c380]Akram Erraqabi, Marlos C. Machado, Mingde Zhao, Sainbayar Sukhbaatar, Alessandro Lazaric, Ludovic Denoyer, Yoshua Bengio:
Temporal abstractions-augmented temporally contrastive learning: An alternative to the Laplacian in RL. UAI 2022: 641-651 - [i434]Ramnath Kumar, Tristan Deleu, Yoshua Bengio:
The Effect of Diversity in Meta-Learning. CoRR abs/2201.11775 (2022) - [i433]Ramnath Kumar, Tristan Deleu, Yoshua Bengio:
Rethinking Learning Dynamics in RL using Adversarial Networks. CoRR abs/2201.11783 (2022) - [i432]Nikolay Malkin, Moksh Jain, Emmanuel Bengio, Chen Sun, Yoshua Bengio:
Trajectory Balance: Improved Credit Assignment in GFlowNets. CoRR abs/2201.13259 (2022) - [i431]Maxence Ernoult, Fabrice Normandin, Abhinav Moudgil, Sean Spinney, Eugene Belilovsky, Irina Rish, Blake A. Richards, Yoshua Bengio:
Towards Scaling Difference Target Propagation by Learning Backprop Targets. CoRR abs/2201.13415 (2022) - [i430]Dianbo Liu, Alex Lamb, Xu Ji, Pascal Notsawo, Michael Mozer, Yoshua Bengio, Kenji Kawaguchi:
Adaptive Discrete Communication Bottlenecks with Dynamic Vector Quantization. CoRR abs/2202.01334 (2022) - [i429]Dinghuai Zhang, Nikolay Malkin, Zhen Liu, Alexandra Volokhova, Aaron C. Courville, Yoshua Bengio:
Generative Flow Networks for Discrete Probabilistic Modeling. CoRR abs/2202.01361 (2022) - [i428]Paul Bertin, Jarrid Rector-Brooks, Deepak Sharma, Thomas Gaudelet, Andrew Anighoro, Torsten Gross, Francisco Martinez-Pena, Eileen L. Tang, Suraj M. S, Cristian Regep, Jeremy B. R. Hayter, Maksym Korablyov, Nicholas Valiante, Almer van der Sloot, Mike Tyers, Charles Roberts, Michael M. Bronstein, Luke L. Lairson, Jake P. Taylor-King, Yoshua Bengio:
RECOVER: sequential model optimization platform for combination drug repurposing identifies novel synergistic compounds in vitro. CoRR abs/2202.04202 (2022) - [i427]Tristan Deleu, António Góis, Chris Emezue, Mansi Rankawat, Simon Lacoste-Julien, Stefan Bauer, Yoshua Bengio:
Bayesian Structure Learning with Generative Flow Networks. CoRR abs/2202.13903 (2022) - [i426]Tristan Deleu, David Kanaa, Leo Feng, Giancarlo Kerg, Yoshua Bengio, Guillaume Lajoie, Pierre-Luc Bacon:
Continuous-Time Meta-Learning with Forward Mode Differentiation. CoRR abs/2203.01443 (2022) - [i425]François St-Hilaire, Dung Do Vu, Antoine Frau, Nathan Burns, Farid Faraji, Joseph Potochny, Stephane Robert, Arnaud Roussel, Selene Zheng, Taylor Glazier, Junfel Vincent Romano, Robert Belfer, Muhammad Shayan, Ariella Smofsky, Tommy Delarosbil, Seulmin Ahn, Simon Eden-Walker, Kritika Sony, Ansona Onyi Ching, Sabina Elkins, Anush Stepanyan, Adela Matajova, Victor Chen, Hossein Sahraei, Robert Larson, Nadia Markova, Andrew Barkett, Laurent Charlin, Yoshua Bengio, Iulian Vlad Serban, Ekaterina Kochmar:
A New Era: Intelligent Tutoring Systems Will Transform Online Learning for Millions. CoRR abs/2203.03724 (2022) - [i424]Moksh Jain, Emmanuel Bengio, Alex Hernández-García, Jarrid Rector-Brooks, Bonaventure F. P. Dossou, Chanakya Ekbote, Jie Fu, Tianyu Zhang, Michael Kilgour, Dinghuai Zhang, Lena Simine, Payel Das, Yoshua Bengio:
Biological Sequence Design with GFlowNets. CoRR abs/2203.04115 (2022) - [i423]Akram Erraqabi, Marlos C. Machado, Mingde Zhao, Sainbayar Sukhbaatar, Alessandro Lazaric, Ludovic Denoyer, Yoshua Bengio:
Temporal Abstractions-Augmented Temporally Contrastive Learning: An Alternative to the Laplacian in RL. CoRR abs/2203.11369 (2022) - [i422]Yoshua Bengio, Prateek Gupta, Dylan R. Radovic, Maarten Scholl, Andrew Williams, Christian Schröder de Witt, Tianyu Zhang, Yang Zhang:
(Private)-Retroactive Carbon Pricing [(P)ReCaP]: A Market-based Approach for Climate Finance and Risk Assessment. CoRR abs/2205.00666 (2022) - [i421]Sanghyun Yoo, Inchul Song, Yoshua Bengio:
A Highly Adaptive Acoustic Model for Accurate Multi-Dialect Speech Recognition. CoRR abs/2205.03027 (2022) - [i420]Mike He Zhu, Léna Néhale Ezzine, Dianbo Liu, Yoshua Bengio:
FedILC: Weighted Geometric Mean and Invariant Gradient Covariance for Federated Learning on Non-IID Data. CoRR abs/2205.09305 (2022) - [i419]Dianbo Liu, Vedant Shah, Oussama Boussif, Cristian Meo, Anirudh Goyal, Tianmin Shu, Michael Mozer, Nicolas Heess, Yoshua Bengio:
Coordinating Policies Among Multiple Agents via an Intelligent Communication Channel. CoRR abs/2205.10607 (2022) - [i418]Sharut Gupta, Kartik Ahuja, Mohammad Havaei, Niladri Chatterjee, Yoshua Bengio:
FL Games: A federated learning framework for distribution shifts. CoRR abs/2205.11101 (2022) - [i417]Aniket Didolkar, Kshitij Gupta, Anirudh Goyal, Alex Lamb, Nan Rosemary Ke, Yoshua Bengio:
Temporal Latent Bottleneck: Synthesis of Fast and Slow Processing Mechanisms in Sequence Learning. CoRR abs/2205.14794 (2022) - [i416]Benjamin Scellier, Siddhartha Mishra, Yoshua Bengio, Yann Ollivier:
Agnostic Physics-Driven Deep Learning. CoRR abs/2205.15021 (2022) - [i415]Kartik Ahuja, Jason S. Hartford, Yoshua Bengio:
Weakly Supervised Representation Learning with Sparse Perturbations. CoRR abs/2206.01101 (2022) - [i414]Sarthak Mittal, Yoshua Bengio, Guillaume Lajoie:
Is a Modular Architecture Enough? CoRR abs/2206.02713 (2022) - [i413]Dinghuai Zhang, Hongyang Zhang, Aaron C. Courville, Yoshua Bengio, Pradeep Ravikumar, Arun Sai Suggala:
Building Robust Ensembles via Margin Boosting. CoRR abs/2206.03362 (2022) - [i412]Nino Scherrer, Anirudh Goyal, Stefan Bauer, Yoshua Bengio, Nan Rosemary Ke:
On the Generalization and Adaption Performance of Causal Models. CoRR abs/2206.04620 (2022) - [i411]Giancarlo Kerg, Sarthak Mittal, David Rolnick, Yoshua Bengio, Blake A. Richards, Guillaume Lajoie:
On Neural Architecture Inductive Biases for Relational Tasks. CoRR abs/2206.05056 (2022) - [i410]Yezhen Wang, Tong Che, Bo Li, Kaitao Song, Hengzhi Pei, Yoshua Bengio, Dongsheng Li:
Your Autoregressive Generative Model Can be Better If You Treat It as an Energy-Based One. CoRR abs/2206.12840 (2022) - [i409]Prateek Gupta, Elias B. Khalil, Didier Chételat, Maxime Gasse, Yoshua Bengio, Andrea Lodi, M. Pawan Kumar:
Lookback for Learning to Branch. CoRR abs/2206.14987 (2022) - [i408]Frederik Träuble, Anirudh Goyal, Nasim Rahaman, Michael Mozer, Kenji Kawaguchi, Yoshua Bengio, Bernhard Schölkopf:
Discrete Key-Value Bottleneck. CoRR abs/2207.11240 (2022) - [i407]Jose Gallego-Posada, Juan Ramirez, Akram Erraqabi, Yoshua Bengio, Simon Lacoste-Julien:
Controlled Sparsity via Constrained Optimization or: How I Learned to Stop Tuning Penalties and Love Constraints. CoRR abs/2208.04425 (2022) - [i406]Siba Moussa, Michael Kilgour, Clara Jans, Alex Hernández-García, Miroslava Cuperlovic-Culf, Yoshua Bengio, Lena Simine:
Diversifying Design of Nucleic Acid Aptamers Using Unsupervised Machine Learning. CoRR abs/2208.05341 (2022) - [i405]Tianyu Zhang, Andrew Williams, Soham Phade, Sunil Srinivasa, Yang Zhang, Prateek Gupta, Yoshua Bengio, Stephan Zheng:
AI for Global Climate Cooperation: Modeling Global Climate Negotiations, Agreements, and Long-Term Cooperation in RICE-N. CoRR abs/2208.07004 (2022) - [i404]Dinghuai Zhang, Ricky T. Q. Chen, Nikolay Malkin, Yoshua Bengio:
Unifying Generative Models with GFlowNets. CoRR abs/2209.02606 (2022) - [i403]Leo Feng, Padideh Nouri, Aneri Muni, Yoshua Bengio, Pierre-Luc Bacon:
Designing Biological Sequences via Meta-Reinforcement Learning and Bayesian Optimization. CoRR abs/2209.06259 (2022) - [i402]Kartik Ahuja, Yixin Wang, Divyat Mahajan, Yoshua Bengio:
Interventional Causal Representation Learning. CoRR abs/2209.11924 (2022) - [i401]Kanika Madan, Jarrid Rector-Brooks, Maksym Korablyov, Emmanuel Bengio, Moksh Jain, Andrei Cristian Nica, Tom Bosc, Yoshua Bengio, Nikolay Malkin:
Learning GFlowNets from partial episodes for improved convergence and stability. CoRR abs/2209.12782 (2022) - [i400]Bonaventure F. P. Dossou, Dianbo Liu, Xu Ji, Moksh Jain, Almer M. van der Sloot, Roger Palou, Michael Tyers, Yoshua Bengio:
Graph-Based Active Machine Learning Method for Diverse and Novel Antimicrobial Peptides Generation and Selection. CoRR abs/2209.13518 (2022) - [i399]Jiaye Teng, Chuan Wen, Dinghuai Zhang, Yoshua Bengio, Yang Gao, Yang Yuan:
Predictive Inference with Feature Conformal Prediction. CoRR abs/2210.00173 (2022) - [i398]Nikolay Malkin, Salem Lahlou, Tristan Deleu, Xu Ji, Edward J. Hu, Katie Everett, Dinghuai Zhang, Yoshua Bengio:
GFlowNets and variational inference. CoRR abs/2210.00580 (2022) - [i397]Dinghuai Zhang, Aaron C. Courville, Yoshua Bengio, Qinqing Zheng, Amy Zhang, Ricky T. Q. Chen:
Latent State Marginalization as a Low-cost Approach for Improving Exploration. CoRR abs/2210.00999 (2022) - [i396]Dianbo Liu, Vedant Shah, Oussama Boussif, Cristian Meo, Anirudh Goyal, Tianmin Shu, Michael Mozer, Nicolas Heess, Yoshua Bengio:
Stateful active facilitator: Coordination and Environmental Heterogeneity in Cooperative Multi-Agent Reinforcement Learning. CoRR abs/2210.03022 (2022) - [i395]Ling Pan, Dinghuai Zhang, Aaron C. Courville, Longbo Huang, Yoshua Bengio:
Generative Augmented Flow Networks. CoRR abs/2210.03308 (2022) - [i394]Oussama Boussif, Dan Assouline, Loubna Benabbou, Yoshua Bengio:
MAgNet: Mesh Agnostic Neural PDE Solver. CoRR abs/2210.05495 (2022) - [i393]Ruixiang Zhang, Tong Che, Boris Ivanovic, Renhao Wang, Marco Pavone, Yoshua Bengio, Liam Paull:
Robust and Controllable Object-Centric Learning through Energy-based Models. CoRR abs/2210.05519 (2022) - [i392]Chen Sun, Wannan Yang, Benjamin Alsbury-Nealy, Yoshua Bengio, Blake A. Richards:
Contrastive introspection (ConSpec) to rapidly identify invariant steps for success. CoRR abs/2210.05845 (2022) - [i391]Nasim Rahaman, Martin Weiss, Francesco Locatello, Chris Pal, Yoshua Bengio, Bernhard Schölkopf, Li Erran Li, Nicolas Ballas:
Neural Attentive Circuits. CoRR abs/2210.08031 (2022) - [i390]Anthony Zador, Blake A. Richards, Bence Ölveczky, Sean Escola, Yoshua Bengio, Kwabena Boahen, Matthew M. Botvinick, Dmitri B. Chklovskii, Anne Churchland, Claudia Clopath, James DiCarlo, Surya Ganguli, Jeff Hawkins, Konrad P. Körding, Alexei A. Koulakov, Yann LeCun, Timothy P. Lillicrap, Adam H. Marblestone, Bruno A. Olshausen, Alexandre Pouget, Cristina Savin, Terrence J. Sejnowski, Eero P. Simoncelli, Sara A. Solla, David Sussillo, Andreas S. Tolias, Doris Tsao:
Toward Next-Generation Artificial Intelligence: Catalyzing the NeuroAI Revolution. CoRR abs/2210.08340 (2022) - [i389]Moksh Jain, Sharath Chandra Raparthy, Alex Hernández-García, Jarrid Rector-Brooks, Yoshua Bengio, Santiago Miret, Emmanuel Bengio:
Multi-Objective GFlowNets. CoRR abs/2210.12765 (2022) - [i388]Dianbo Liu, Moksh Jain, Bonaventure Dossou, Qianli Shen, Salem Lahlou, Anirudh Goyal, Nikolay Malkin, Chris Emezue, Dinghuai Zhang, Nadhir Hassen, Xu Ji, Kenji Kawaguchi, Yoshua Bengio:
GFlowOut: Dropout with Generative Flow Networks. CoRR abs/2210.12928 (2022) - [i387]Sharut Gupta, Kartik Ahuja, Mohammad Havaei, Niladri Chatterjee, Yoshua Bengio:
FL Games: A Federated Learning Framework for Distribution Shifts. CoRR abs/2211.00184 (2022) - [i386]Riashat Islam, Hongyu Zang, Anirudh Goyal, Alex Lamb, Kenji Kawaguchi, Xin Li, Romain Laroche, Yoshua Bengio, Remi Tachet des Combes:
Discrete Factorial Representations as an Abstraction for Goal Conditioned Reinforcement Learning. CoRR abs/2211.00247 (2022) - [i385]Chanakya Ekbote, Moksh Jain, Payel Das, Yoshua Bengio:
Consistent Training via Energy-Based GFlowNets for Modeling Discrete Joint Distributions. CoRR abs/2211.00568 (2022) - [i384]Nasim Rahaman, Martin Weiss, Frederik Träuble, Francesco Locatello, Alexandre Lacoste, Yoshua Bengio, Chris Pal, Li Erran Li, Bernhard Schölkopf:
A General Purpose Neural Architecture for Geospatial Systems. CoRR abs/2211.02348 (2022) - [i383]Mizu Nishikawa-Toomey, Tristan Deleu, Jithendaraa Subramanian, Yoshua Bengio, Laurent Charlin:
Bayesian learning of Causal Structure and Mechanisms with GFlowNets and Variational Bayes. CoRR abs/2211.02763 (2022) - [i382]Alexandre Adam, Adam Coogan, Nikolay Malkin, Ronan Legin, Laurence Perreault Levasseur, Yashar Hezaveh, Yoshua Bengio:
Posterior samples of source galaxies in strong gravitational lenses with score-based priors. CoRR abs/2211.03812 (2022) - [i381]Sékou-Oumar Kaba, Arnab Kumar Mondal, Yan Zhang, Yoshua Bengio, Siamak Ravanbakhsh:
Equivariance with Learned Canonicalization Functions. CoRR abs/2211.06489 (2022) - [i380]Leo Feng, Hossein Hajimirsadeghi, Yoshua Bengio, Mohamed Osama Ahmed:
Latent Bottlenecked Attentive Neural Processes. CoRR abs/2211.08458 (2022) - [i379]Alexandre Duval, Victor Schmidt, Santiago Miret, Yoshua Bengio, Alex Hernández-García, David Rolnick:
PhAST: Physics-Aware, Scalable, and Task-specific GNNs for Accelerated Catalyst Design. CoRR abs/2211.12020 (2022) - [i378]Sébastien Lachapelle, Tristan Deleu, Divyat Mahajan, Ioannis Mitliagkas, Yoshua Bengio, Simon Lacoste-Julien, Quentin Bertrand:
Synergies Between Disentanglement and Sparsity: a Multi-Task Learning Perspective. CoRR abs/2211.14666 (2022) - [i377]Vikas Verma, Sarthak Mittal, Wai Hoh Tang, Hieu Pham, Juho Kannala, Yoshua Bengio, Arno Solin, Kenji Kawaguchi:
MixupE: Understanding and Improving Mixup from Directional Derivative Perspective. CoRR abs/2212.13381 (2022) - 2021
- [j108]Yoshua Bengio, Yann LeCun, Geoffrey E. Hinton:
Deep learning for AI. Commun. ACM 64(7): 58-65 (2021) - [j107]Alexandra Luccioni, Victor Schmidt, Vahe Vardanyan, Yoshua Bengio, Theresa-Marie Rhyne:
Using Artificial Intelligence to Visualize the Impacts of Climate Change. IEEE Computer Graphics and Applications 41(1): 8-14 (2021) - [j106]Yoshua Bengio, Andrea Lodi, Antoine Prouvost:
Machine learning for combinatorial optimization: A methodological tour d'horizon. Eur. J. Oper. Res. 290(2): 405-421 (2021) - [j105]Yoshua Bengio, Daphne Ippolito, Richard Janda, Max Jarvie, Benjamin Prud'homme, Jean-Franois Rousseau, Abhinav Sharma, Yun William Yu:
Inherent privacy limitations of decentralized contact tracing apps. J. Am. Medical Informatics Assoc. 28(1): 193-195 (2021) - [j104]Bernhard Schölkopf, Francesco Locatello, Stefan Bauer, Nan Rosemary Ke, Nal Kalchbrenner, Anirudh Goyal, Yoshua Bengio:
Toward Causal Representation Learning. Proc. IEEE 109(5): 612-634 (2021) - [j103]Tariq Daouda, Maude Dumont-Lagacé, Albert Feghaly, Yahya Benslimane, Rébecca Panes, Mathieu Courcelles, Mohamed Benhammadi, Lea Harrington, Pierre Thibault, François Major, Yoshua Bengio, Etienne Gagnon, Sébastien Lemieux, Claude Perreault:
CAMAP: Artificial neural networks unveil the role of codon arrangement in modulating MHC-I peptides presentation. PLoS Comput. Biol. 17(10) (2021) - [c379]Tristan Sylvain, Pengchuan Zhang, Yoshua Bengio, R. Devon Hjelm, Shikhar Sharma:
Object-Centric Image Generation from Layouts. AAAI 2021: 2647-2655 - [c378]Giulia Zarpellon, Jason Jo, Andrea Lodi, Yoshua Bengio:
Parameterizing Branch-and-Bound Search Trees to Learn Branching Policies. AAAI 2021: 3931-3939 - [c377]Tong Che, Xiaofeng Liu, Site Li, Yubin Ge, Ruixiang Zhang, Caiming Xiong, Yoshua Bengio:
Deep Verifier Networks: Verification of Deep Discriminative Models with Deep Generative Models. AAAI 2021: 7002-7010 - [c376]Taesup Kim, Sungwoong Kim, Yoshua Bengio:
Visual Concept Reasoning Networks. AAAI 2021: 8172-8180 - [c375]Boris N. Oreshkin, Dmitri Carpov, Nicolas Chapados, Yoshua Bengio:
Meta-Learning Framework with Applications to Zero-Shot Time-Series Forecasting. AAAI 2021: 9242-9250 - [c374]Vikas Verma, Meng Qu, Kenji Kawaguchi, Alex Lamb, Yoshua Bengio, Juho Kannala, Jian Tang:
GraphMix: Improved Training of GNNs for Semi-Supervised Learning. AAAI 2021: 10024-10032 - [c373]François St-Hilaire, Nathan Burns, Robert Belfer, Muhammad Shayan, Ariella Smofsky, Dung Do Vu, Antoine Frau, Joseph Potochny, Farid Faraji, Vincent Pavero, Neroli Ko, Ansona Onyi Ching, Sabina Elkins, Anush Stepanyan, Adela Matajova, Laurent Charlin, Yoshua Bengio, Iulian Vlad Serban, Ekaterina Kochmar:
A Comparative Study of Learning Outcomes for Online Learning Platforms. AIED (2) 2021: 331-337 - [c372]Rémi Le Priol, Reza Babanezhad, Yoshua Bengio, Simon Lacoste-Julien:
An Analysis of the Adaptation Speed of Causal Models. AISTATS 2021: 775-783 - [c371]Alex Lamb, Anirudh Goyal, Agnieszka Slowik, Michael Mozer, Philippe Beaudoin, Yoshua Bengio:
Neural Function Modules with Sparse Arguments: A Dynamic Approach to Integrating Information across Layers. AISTATS 2021: 919-927 - [c370]Tristan Sylvain, Francis Dutil, Tess Berthier, Lisa Di-Jorio, Margaux Luck, R. Devon Hjelm, Yoshua Bengio:
CMIM: Cross-Modal Information Maximization For Medical Imaging. ICASSP 2021: 1190-1194 - [c369]Yuwei Cheng, Jiannan Zhu, Mengxin Jiang, Jie Fu, Changsong Pang, Peidong Wang, Kris Sankaran, Olawale Onabola, Yimin Liu, Dianbo Liu, Yoshua Bengio:
FloW: A Dataset and Benchmark for Floating Waste Detection in Inland Waters. ICCV 2021: 10933-10942 - [c368]Faruk Ahmed, Yoshua Bengio, Harm van Seijen, Aaron C. Courville:
Systematic generalisation with group invariant predictions. ICLR 2021 - [c367]Ossama Ahmed, Frederik Träuble, Anirudh Goyal, Alexander Neitz, Manuel Wuthrich, Yoshua Bengio, Bernhard Schölkopf, Stefan Bauer:
CausalWorld: A Robotic Manipulation Benchmark for Causal Structure and Transfer Learning. ICLR 2021 - [c366]Yoshua Bengio, Prateek Gupta, Tegan Maharaj, Nasim Rahaman, Martin Weiss, Tristan Deleu, Eilif Benjamin Müller, Meng Qu, Victor Schmidt, Pierre-Luc St-Charles, Hannah Alsdurf, Olexa Bilaniuk, David L. Buckeridge, Gaétan Marceau-Caron, Pierre Luc Carrier, Joumana Ghosn, Satya Ortiz-Gagne, Christopher J. Pal, Irina Rish, Bernhard Schölkopf, Abhinav Sharma, Jian Tang, Andrew Williams:
Predicting Infectiousness for Proactive Contact Tracing. ICLR 2021 - [c365]Anirudh Goyal, Alex Lamb, Phanideep Gampa, Philippe Beaudoin, Charles Blundell, Sergey Levine, Yoshua Bengio, Michael Curtis Mozer:
Factorizing Declarative and Procedural Knowledge in Structured, Dynamical Environments. ICLR 2021 - [c364]Anirudh Goyal, Alex Lamb, Jordan Hoffmann, Shagun Sodhani, Sergey Levine, Yoshua Bengio, Bernhard Schölkopf:
Recurrent Independent Mechanisms. ICLR 2021 - [c363]Kanika Madan, Nan Rosemary Ke, Anirudh Goyal, Bernhard Schölkopf, Yoshua Bengio:
Fast And Slow Learning Of Recurrent Independent Mechanisms. ICLR 2021 - [c362]Meng Qu, Junkun Chen, Louis-Pascal A. C. Xhonneux, Yoshua Bengio, Jian Tang:
RNNLogic: Learning Logic Rules for Reasoning on Knowledge Graphs. ICLR 2021 - [c361]Nasim Rahaman, Anirudh Goyal, Muhammad Waleed Gondal, Manuel Wuthrich, Stefan Bauer, Yash Sharma, Yoshua Bengio, Bernhard Schölkopf:
Spatially Structured Recurrent Modules. ICLR 2021 - [c360]Joseph D. Viviano, Becks Simpson, Francis Dutil, Yoshua Bengio, Joseph Paul Cohen:
Saliency is a Possible Red Herring When Diagnosing Poor Generalization. ICLR 2021 - [c359]Minkai Xu, Shitong Luo, Yoshua Bengio, Jian Peng, Jian Tang:
Learning Neural Generative Dynamics for Molecular Conformation Generation. ICLR 2021 - [c358]Minkai Xu, Wujie Wang, Shitong Luo, Chence Shi, Yoshua Bengio, Rafael Gómez-Bombarelli, Jian Tang:
An End-to-End Framework for Molecular Conformation Generation via Bilevel Programming. ICML 2021: 11537-11547 - [c357]Konrad Zolna, Chitwan Saharia, Léonard Boussioux, David Yu-Tung Hui, Maxime Chevalier-Boisvert, Dzmitry Bahdanau, Yoshua Bengio:
Combating False Negatives in Adversarial Imitation Learning. IJCNN 2021: 1-9 - [c356]Olawale Onabola, Zhuang Ma, Yang Xie, Benjamin Akera, Abdulrahman Ibraheem, Jia Xue, Dianbo Liu, Yoshua Bengio:
hBERT + BiasCorp - Fighting Racism on the Web. LT-EDI@EACL 2021: 26-33 - [c355]Nan Rosemary Ke, Aniket Didolkar, Sarthak Mittal, Anirudh Goyal, Guillaume Lajoie, Stefan Bauer, Danilo Jimenez Rezende, Michael Mozer, Yoshua Bengio, Chris Pal:
Systematic Evaluation of Causal Discovery in Visual Model Based Reinforcement Learning. NeurIPS Datasets and Benchmarks 2021 - [c354]Mohammad Pezeshki, Sékou-Oumar Kaba, Yoshua Bengio, Aaron C. Courville, Doina Precup, Guillaume Lajoie:
Gradient Starvation: A Learning Proclivity in Neural Networks. NeurIPS 2021: 1256-1272 - [c353]Mingde Zhao, Zhen Liu, Sitao Luan, Shuyuan Zhang, Doina Precup, Yoshua Bengio:
A Consciousness-Inspired Planning Agent for Model-Based Reinforcement Learning. NeurIPS 2021: 1569-1581 - [c352]Dianbo Liu, Alex Lamb, Kenji Kawaguchi, Anirudh Goyal, Chen Sun, Michael C. Mozer, Yoshua Bengio:
Discrete-Valued Neural Communication. NeurIPS 2021: 2109-2121 - [c351]Kartik Ahuja, Ethan Caballero, Dinghuai Zhang, Jean-Christophe Gagnon-Audet, Yoshua Bengio, Ioannis Mitliagkas, Irina Rish:
Invariance Principle Meets Information Bottleneck for Out-of-Distribution Generalization. NeurIPS 2021: 3438-3450 - [c350]Kevin Xia, Kai-Zhan Lee, Yoshua Bengio, Elias Bareinboim:
The Causal-Neural Connection: Expressiveness, Learnability, and Inference. NeurIPS 2021: 10823-10836 - [c349]Nasim Rahaman, Muhammad Waleed Gondal, Shruti Joshi, Peter V. Gehler, Yoshua Bengio, Francesco Locatello, Bernhard Schölkopf:
Dynamic Inference with Neural Interpreters. NeurIPS 2021: 10985-10998 - [c348]Aniket Didolkar, Anirudh Goyal, Nan Rosemary Ke, Charles Blundell, Philippe Beaudoin, Nicolas Heess, Michael Mozer, Yoshua Bengio:
Neural Production Systems. NeurIPS 2021: 25673-25687 - [c347]Emmanuel Bengio, Moksh Jain, Maksym Korablyov, Doina Precup, Yoshua Bengio:
Flow Network based Generative Models for Non-Iterative Diverse Candidate Generation. NeurIPS 2021: 27381-27394 - [c346]Tristan Sylvain, Margaux Luck, Joseph Paul Cohen, Héloïse Cardinal, Andrea Lodi, Yoshua Bengio:
Exploring the Wasserstein metric for time-to-event analysis. SPACA 2021: 194-206 - [i376]Axel Laborieux, Maxence Ernoult, Benjamin Scellier, Yoshua Bengio, Julie Grollier, Damien Querlioz:
Scaling Equilibrium Propagation to Deep ConvNets by Drastically Reducing its Gradient Estimator Bias. CoRR abs/2101.05536 (2021) - [i375]Tristan Deleu, Yoshua Bengio:
Structured Sparsity Inducing Adaptive Optimizers for Deep Learning. CoRR abs/2102.03869 (2021) - [i374]Moksh Jain, Salem Lahlou, Hadi Nekoei, Victor Butoi, Paul Bertin, Jarrid Rector-Brooks, Maksym Korablyov, Yoshua Bengio:
DEUP: Direct Epistemic Uncertainty Prediction. CoRR abs/2102.08501 (2021) - [i373]Minkai Xu, Shitong Luo, Yoshua Bengio, Jian Peng, Jian Tang:
Learning Neural Generative Dynamics for Molecular Conformation Generation. CoRR abs/2102.10240 (2021) - [i372]Bernhard Schölkopf, Francesco Locatello, Stefan Bauer, Nan Rosemary Ke, Nal Kalchbrenner, Anirudh Goyal, Yoshua Bengio:
Towards Causal Representation Learning. CoRR abs/2102.11107 (2021) - [i371]Alex Lamb, Di He, Anirudh Goyal, Guolin Ke, Chien-Feng Liao, Mirco Ravanelli, Yoshua Bengio:
Transformers with Competitive Ensembles of Independent Mechanisms. CoRR abs/2103.00336 (2021) - [i370]Anirudh Goyal, Aniket Didolkar, Alex Lamb, Kartikeya Badola, Nan Rosemary Ke, Nasim Rahaman, Jonathan Binas, Charles Blundell, Michael Mozer, Yoshua Bengio:
Coordination Among Neural Modules Through a Shared Global Workspace. CoRR abs/2103.01197 (2021) - [i369]Anirudh Goyal, Aniket Didolkar, Nan Rosemary Ke, Charles Blundell, Philippe Beaudoin, Nicolas Heess, Michael Mozer, Yoshua Bengio:
Neural Production Systems. CoRR abs/2103.01937 (2021) - [i368]Olawale Onabola, Zhuang Ma, Yang Xie, Benjamin Akera, Abdulrahman Ibraheem, Jia Xue, Dianbo Liu, Yoshua Bengio:
hBert + BiasCorp - Fighting Racism on the Web. CoRR abs/2104.02242 (2021) - [i367]François St-Hilaire, Nathan Burns, Robert Belfer, Muhammad Shayan, Ariella Smofsky, Dung Do Vu, Antoine Frau, Joseph Potochny, Farid Faraji, Vincent Pavero, Neroli Ko, Ansona Onyi Ching, Sabina Elkins, Anush Stepanyan, Adela Matajova, Laurent Charlin, Yoshua Bengio, Iulian Vlad Serban, Ekaterina Kochmar:
Comparative Study of Learning Outcomes for Online Learning Platforms. CoRR abs/2104.07763 (2021) - [i366]Minkai Xu, Wujie Wang, Shitong Luo, Chence Shi, Yoshua Bengio, Rafael Gómez-Bombarelli, Jian Tang:
An End-to-End Framework for Molecular Conformation Generation via Bilevel Programming. CoRR abs/2105.07246 (2021) - [i365]Kanika Madan, Nan Rosemary Ke, Anirudh Goyal, Bernhard Schölkopf, Yoshua Bengio:
Fast and Slow Learning of Recurrent Independent Mechanisms. CoRR abs/2105.08710 (2021) - [i364]Mingde Zhao, Zhen Liu, Sitao Luan, Shuyuan Zhang, Doina Precup, Yoshua Bengio:
A Consciousness-Inspired Planning Agent for Model-Based Reinforcement Learning. CoRR abs/2106.02097 (2021) - [i363]Emmanuel Bengio, Moksh Jain, Maksym Korablyov, Doina Precup, Yoshua Bengio:
Flow Network based Generative Models for Non-Iterative Diverse Candidate Generation. CoRR abs/2106.04399 (2021) - [i362]Mirco Ravanelli, Titouan Parcollet, Peter Plantinga, Aku Rouhe, Samuele Cornell, Loren Lugosch, Cem Subakan, Nauman Dawalatabad, Abdelwahab Heba, Jianyuan Zhong, Ju-Chieh Chou, Sung-Lin Yeh, Szu-Wei Fu, Chien-Feng Liao, Elena Rastorgueva, François Grondin, William Aris, Hwidong Na, Yan Gao, Renato De Mori, Yoshua Bengio:
SpeechBrain: A General-Purpose Speech Toolkit. CoRR abs/2106.04624 (2021) - [i361]Kartik Ahuja, Ethan Caballero, Dinghuai Zhang, Yoshua Bengio, Ioannis Mitliagkas, Irina Rish:
Invariance Principle Meets Information Bottleneck for Out-of-Distribution Generalization. CoRR abs/2106.06607 (2021) - [i360]Yashas Annadani, Jonas Rothfuss, Alexandre Lacoste, Nino Scherrer, Anirudh Goyal, Yoshua Bengio, Stefan Bauer:
Variational Causal Networks: Approximate Bayesian Inference over Causal Structures. CoRR abs/2106.07635 (2021) - [i359]Xu Ji, Razvan Pascanu, R. Devon Hjelm, Andrea Vedaldi, Balaji Lakshminarayanan, Yoshua Bengio:
Predicting Unreliable Predictions by Shattering a Neural Network. CoRR abs/2106.08365 (2021) - [i358]Kevin Xia, Kai-Zhan Lee, Yoshua Bengio, Elias Bareinboim:
The Causal-Neural Connection: Expressiveness, Learnability, and Inference. CoRR abs/2107.00793 (2021) - [i357]Nan Rosemary Ke, Aniket Didolkar, Sarthak Mittal, Anirudh Goyal, Guillaume Lajoie, Stefan Bauer, Danilo J. Rezende, Yoshua Bengio, Michael Mozer, Christopher J. Pal:
Systematic Evaluation of Causal Discovery in Visual Model Based Reinforcement Learning. CoRR abs/2107.00848 (2021) - [i356]Dianbo Liu, Alex Lamb, Kenji Kawaguchi, Anirudh Goyal, Chen Sun, Michael Curtis Mozer, Yoshua Bengio:
Discrete-Valued Neural Communication. CoRR abs/2107.02367 (2021) - [i355]Nino Scherrer, Olexa Bilaniuk, Yashas Annadani, Anirudh Goyal, Patrick Schwab, Bernhard Schölkopf, Michael C. Mozer, Yoshua Bengio, Stefan Bauer, Nan Rosemary Ke:
Learning Neural Causal Models with Active Interventions. CoRR abs/2109.02429 (2021) - [i354]Victor Schmidt, Alexandra Sasha Luccioni, Mélisande Teng, Tianyu Zhang, Alexia Reynaud, Sunand Raghupathi, Gautier Cosne, Adrien Juraver, Vahe Vardanyan, Alex Hernández-García, Yoshua Bengio:
ClimateGAN: Raising Climate Change Awareness by Generating Images of Floods. CoRR abs/2110.02871 (2021) - [i353]Dinghuai Zhang, Jie Fu, Yoshua Bengio, Aaron C. Courville:
Unifying Likelihood-free Inference with Black-box Sequence Design and Beyond. CoRR abs/2110.03372 (2021) - [i352]Nasim Rahaman, Muhammad Waleed Gondal, Shruti Joshi, Peter V. Gehler, Yoshua Bengio, Francesco Locatello, Bernhard Schölkopf:
Dynamic Inference with Neural Interpreters. CoRR abs/2110.06399 (2021) - [i351]Vijay Prakash Dwivedi, Anh Tuan Luu, Thomas Laurent, Yoshua Bengio, Xavier Bresson:
Graph Neural Networks with Learnable Structural and Positional Representations. CoRR abs/2110.07875 (2021) - [i350]Sarthak Mittal, Sharath Chandra Raparthy, Irina Rish, Yoshua Bengio, Guillaume Lajoie:
Compositional Attention: Disentangling Search and Retrieval. CoRR abs/2110.09419 (2021) - [i349]Max Morrison, Rithesh Kumar, Kundan Kumar, Prem Seetharaman, Aaron C. Courville, Yoshua Bengio:
Chunked Autoregressive GAN for Conditional Waveform Synthesis. CoRR abs/2110.10139 (2021) - [i348]Nicholas Roy, Ingmar Posner, Tim D. Barfoot, Philippe Beaudoin, Yoshua Bengio, Jeannette Bohg, Oliver Brock, Isabelle Depatie, Dieter Fox, Daniel E. Koditschek, Tomás Lozano-Pérez, Vikash Mansinghka, Christopher J. Pal, Blake A. Richards, Dorsa Sadigh, Stefan Schaal, Gaurav S. Sukhatme, Denis Thérien, Marc Toussaint, Michiel van de Panne:
From Machine Learning to Robotics: Challenges and Opportunities for Embodied Intelligence. CoRR abs/2110.15245 (2021) - [i347]Kartik Ahuja, Jason S. Hartford, Yoshua Bengio:
Properties from Mechanisms: An Equivariance Perspective on Identifiable Representation Learning. CoRR abs/2110.15796 (2021) - [i346]Yoshua Bengio, Tristan Deleu, Edward J. Hu, Salem Lahlou, Mo Tiwari, Emmanuel Bengio:
GFlowNet Foundations. CoRR abs/2111.09266 (2021) - [i345]Mohammad Pezeshki, Amartya Mitra, Yoshua Bengio, Guillaume Lajoie:
Multi-scale Feature Learning Dynamics: Insights for Double Descent. CoRR abs/2112.03215 (2021) - [i344]Enoch Tetteh, Joseph D. Viviano, Yoshua Bengio, David Krueger, Joseph Paul Cohen:
Multi-Domain Balanced Sampling Improves Out-of-Distribution Generalization of Chest X-ray Pathology Prediction Models. CoRR abs/2112.13734 (2021) - 2020
- [j102]ByungIn Yoo, Tristan Sylvain, Yoshua Bengio, Junmo Kim:
Joint Learning of Generative Translator and Classifier for Visually Similar Classes. IEEE Access 8: 219160-219173 (2020) - [j101]Assya Trofimov, Joseph Paul Cohen, Yoshua Bengio, Claude Perreault, Sébastien Lemieux:
Factorized embeddings learns rich and biologically meaningful embedding spaces using factorized tensor decomposition. Bioinform. 36(Supplement-1): i417-i426 (2020) - [j100]Ian J. Goodfellow, Jean Pouget-Abadie, Mehdi Mirza, Bing Xu, David Warde-Farley, Sherjil Ozair, Aaron C. Courville, Yoshua Bengio:
Generative adversarial networks. Commun. ACM 63(11): 139-144 (2020) - [j99]Iulian Vlad Serban, Chinnadhurai Sankar, Michael Pieper, Joelle Pineau, Yoshua Bengio:
The Bottleneck Simulator: A Model-Based Deep Reinforcement Learning Approach. J. Artif. Intell. Res. 69: 571-612 (2020) - [j98]Sharon Zhou, Alexandra Luccioni, Gautier Cosne, Michael S. Bernstein, Yoshua Bengio:
Establishing an evaluation metric to quantify climate change image realism. Mach. Learn. Sci. Technol. 1(2): 25005 (2020) - [j97]Shagun Sodhani, Sarath Chandar, Yoshua Bengio:
Toward Training Recurrent Neural Networks for Lifelong Learning. Neural Comput. 32(1): 1-35 (2020) - [j96]Alexandra Luccioni, Yoshua Bengio:
On the Morality of Artificial Intelligence [Commentary]. IEEE Technol. Soc. Mag. 39(1): 16-25 (2020) - [c345]Konrad Zolna, Chitwan Saharia, Léonard Boussioux, David Yu-Tung Hui, Maxime Chevalier-Boisvert, Dzmitry Bahdanau, Yoshua Bengio:
Combating False Negatives in Adversarial Imitation Learning (Student Abstract). AAAI 2020: 13999-14000 - [c344]Jacob L. Russin, Jason Jo, Randall C. O'Reilly, Yoshua Bengio:
Compositional Generalization by Factorizing Alignment and Translation. ACL (student) 2020: 313-327 - [c343]Wenyu Du, Zhouhan Lin, Yikang Shen, Timothy J. O'Donnell, Yoshua Bengio, Yue Zhang:
Exploiting Syntactic Structure for Better Language Modeling: A Syntactic Distance Approach. ACL 2020: 6611-6628 - [c342]Iulian Vlad Serban, Varun Gupta, Ekaterina Kochmar, Dung Do Vu, Robert Belfer, Joelle Pineau, Aaron C. Courville, Laurent Charlin, Yoshua Bengio:
A Large-Scale, Open-Domain, Mixed-Interface Dialogue-Based ITS for STEM. AIED (2) 2020: 387-392 - [c341]Valentin Thomas, Fabian Pedregosa, Bart van Merriënboer, Pierre-Antoine Manzagol, Yoshua Bengio, Nicolas Le Roux:
On the interplay between noise and curvature and its effect on optimization and generalization. AISTATS 2020: 3503-3513 - [c340]Jacob L. Russin, Jason Jo, Randall C. O'Reilly, Yoshua Bengio:
Systematicity in a Recurrent Neural Network by Factorizing Syntax and Semantics. CogSci 2020 - [c339]Yoshua Bengio, Emma Frejinger, Andrea Lodi, Rahul Patel, Sriram Sankaranarayanan:
A Learning-Based Algorithm to Quickly Compute Good Primal Solutions for Stochastic Integer Programs. CPAIOR 2020: 99-111 - [c338]Md Rifat Arefin, Vincent Michalski, Pierre-Luc St-Charles, Alfredo Kalaitzis, Sookyung Kim, Samira Ebrahimi Kahou, Yoshua Bengio:
Multi-Image Super-Resolution for Remote Sensing using Deep Recurrent Networks. CVPR Workshops 2020: 816-825 - [c337]Timo Milbich, Karsten Roth, Homanga Bharadhwaj, Samarth Sinha, Yoshua Bengio, Björn Ommer, Joseph Paul Cohen:
DiVA: Diverse Visual Feature Aggregation for Deep Metric Learning. ECCV (8) 2020: 590-607 - [c336]Yonatan Bisk, Ari Holtzman, Jesse Thomason, Jacob Andreas, Yoshua Bengio, Joyce Chai, Mirella Lapata, Angeliki Lazaridou, Jonathan May, Aleksandr Nisnevich, Nicolas Pinto, Joseph P. Turian:
Experience Grounds Language. EMNLP (1) 2020: 8718-8735 - [c335]Mirco Ravanelli, Jianyuan Zhong, Santiago Pascual, Pawel Swietojanski, João Monteiro, Jan Trmal, Yoshua Bengio:
Multi-Task Self-Supervised Learning for Robust Speech Recognition. ICASSP 2020: 6989-6993 - [c334]Yoshua Bengio, Tristan Deleu, Nasim Rahaman, Nan Rosemary Ke, Sébastien Lachapelle, Olexa Bilaniuk, Anirudh Goyal, Christopher J. Pal:
A Meta-Transfer Objective for Learning to Disentangle Causal Mechanisms. ICLR 2020 - [c333]Anirudh Goyal, Yoshua Bengio, Matthew M. Botvinick, Sergey Levine:
The Variational Bandwidth Bottleneck: Stochastic Evaluation on an Information Budget. ICLR 2020 - [c332]Anirudh Goyal, Shagun Sodhani, Jonathan Binas, Xue Bin Peng, Sergey Levine, Yoshua Bengio:
Reinforcement Learning with Competitive Ensembles of Information-Constrained Primitives. ICLR 2020 - [c331]Boris N. Oreshkin, Dmitri Carpov, Nicolas Chapados, Yoshua Bengio:
N-BEATS: Neural basis expansion analysis for interpretable time series forecasting. ICLR 2020 - [c330]Nasim Rahaman, Steffen Wolf, Anirudh Goyal, Roman Remme, Yoshua Bengio:
Learning the Arrow of Time for Problems in Reinforcement Learning. ICLR 2020 - [c329]William Fedus, Prajit Ramachandran, Rishabh Agarwal, Yoshua Bengio, Hugo Larochelle, Mark Rowland, Will Dabney:
Revisiting Fundamentals of Experience Replay. ICML 2020: 3061-3071 - [c328]Sai Krishna Gottipati, Boris Sattarov, Sufeng Niu, Yashaswi Pathak, Haoran Wei, Shengchao Liu, Simon Blackburn, Karam M. J. Thomas, Connor W. Coley, Jian Tang, Sarath Chandar, Yoshua Bengio:
Learning to Navigate The Synthetically Accessible Chemical Space Using Reinforcement Learning. ICML 2020: 3668-3679 - [c327]Sarthak Mittal, Alex Lamb, Anirudh Goyal, Vikram Voleti, Murray Shanahan, Guillaume Lajoie, Michael Mozer, Yoshua Bengio:
Learning to Combine Top-Down and Bottom-Up Signals in Recurrent Neural Networks with Attention over Modules. ICML 2020: 6972-6986 - [c326]Samarth Sinha, Han Zhang, Anirudh Goyal, Yoshua Bengio, Hugo Larochelle, Augustus Odena:
Small-GAN: Speeding up GAN Training using Core-Sets. ICML 2020: 9005-9015 - [c325]Zijun Zhang, Ruixiang Zhang, Zongpeng Li, Yoshua Bengio, Liam Paull:
Perceptual Generative Autoencoders. ICML 2020: 11298-11306 - [c324]Ghouthi Boukli Hacene, Carlos Lassance, Vincent Gripon, Matthieu Courbariaux, Yoshua Bengio:
Attention Based Pruning for Shift Networks. ICPR 2020: 4054-4061 - [c323]Ghouthi Boukli Hacene, Vincent Gripon, Matthieu Arzel, Nicolas Farrugia, Yoshua Bengio:
Quantized Guided Pruning for Efficient Hardware Implementations of Deep Neural Networks. NEWCAS 2020: 206-209 - [c322]Tong Che, Ruixiang Zhang, Jascha Sohl-Dickstein, Hugo Larochelle, Liam Paull, Yuan Cao, Yoshua Bengio:
Your GAN is Secretly an Energy-based Model and You Should Use Discriminator Driven Latent Sampling. NeurIPS 2020 - [c321]Prateek Gupta, Maxime Gasse, Elias B. Khalil, Pawan Kumar Mudigonda, Andrea Lodi, Yoshua Bengio:
Hybrid Models for Learning to Branch. NeurIPS 2020 - [c320]Giancarlo Kerg, Bhargav Kanuparthi, Anirudh Goyal, Kyle Goyette, Yoshua Bengio, Guillaume Lajoie:
Untangling tradeoffs between recurrence and self-attention in artificial neural networks. NeurIPS 2020 - [i343]Travis LaCroix, Yoshua Bengio:
Learning from Learning Machines: Optimisation, Rules, and Social Norms. CoRR abs/2001.00006 (2020) - [i342]Chen Ma, Dylan R. Ashley, Junfeng Wen, Yoshua Bengio:
Universal Successor Features for Transfer Reinforcement Learning. CoRR abs/2001.04025 (2020) - [i341]Mirco Ravanelli, Jianyuan Zhong, Santiago Pascual, Pawel Swietojanski, João Monteiro, Jan Trmal, Yoshua Bengio:
Multi-task self-supervised learning for Robust Speech Recognition. CoRR abs/2001.09239 (2020) - [i340]Gautier Cosne, Adrien Juraver, Mélisande Teng, Victor Schmidt, Vahe Vardanyan, Alexandra Luccioni, Yoshua Bengio:
Using Simulated Data to Generate Images of Climate Change. CoRR abs/2001.09531 (2020) - [i339]Konrad Zolna, Chitwan Saharia, Léonard Boussioux, David Yu-Tung Hui, Maxime Chevalier-Boisvert, Dzmitry Bahdanau, Yoshua Bengio:
Combating False Negatives in Adversarial Imitation Learning. CoRR abs/2002.00412 (2020) - [i338]Boris N. Oreshkin, Dmitri Carpov, Nicolas Chapados, Yoshua Bengio:
Meta-learning framework with applications to zero-shot time-series forecasting. CoRR abs/2002.02887 (2020) - [i337]Milos Nikolic, Ghouthi Boukli Hacene, Ciaran Bannon, Alberto Delmas Lascorz, Matthieu Courbariaux, Yoshua Bengio, Vincent Gripon, Andreas Moshovos:
BitPruning: Learning Bitlengths for Aggressive and Accurate Quantization. CoRR abs/2002.03090 (2020) - [i336]Giulia Zarpellon, Jason Jo, Andrea Lodi, Yoshua Bengio:
Parameterizing Branch-and-Bound Search Trees to Learn Branching Policies. CoRR abs/2002.05120 (2020) - [i335]Michel Deudon, Alfredo Kalaitzis, Israel Goytom, Md Rifat Arefin, Zhichao Lin, Kris Sankaran, Vincent Michalski, Samira Ebrahimi Kahou, Julien Cornebise, Yoshua Bengio:
HighRes-net: Recursive Fusion for Multi-Frame Super-Resolution of Satellite Imagery. CoRR abs/2002.06460 (2020) - [i334]Devansh Arpit, Huan Wang, Caiming Xiong, Richard Socher, Yoshua Bengio:
Neural Bayes: A Generic Parameterization Method for Unsupervised Representation Learning. CoRR abs/2002.09046 (2020) - [i333]William Fedus, Dibya Ghosh, John D. Martin, Marc G. Bellemare, Yoshua Bengio, Hugo Larochelle:
On Catastrophic Interference in Atari 2600 Games. CoRR abs/2002.12499 (2020) - [i332]Vijay Prakash Dwivedi, Chaitanya K. Joshi, Thomas Laurent, Yoshua Bengio, Xavier Bresson:
Benchmarking Graph Neural Networks. CoRR abs/2003.00982 (2020) - [i331]Qicheng Lao, Xiang Jiang, Mohammad Havaei, Yoshua Bengio:
Continuous Domain Adaptation with Variational Domain-Agnostic Feature Replay. CoRR abs/2003.04382 (2020) - [i330]Tong Che, Ruixiang Zhang, Jascha Sohl-Dickstein, Hugo Larochelle, Liam Paull, Yuan Cao, Yoshua Bengio:
Your GAN is Secretly an Energy-based Model and You Should use Discriminator Driven Latent Sampling. CoRR abs/2003.06060 (2020) - [i329]Tristan Sylvain, Pengchuan Zhang, Yoshua Bengio, R. Devon Hjelm, Shikhar Sharma:
Object-Centric Image Generation from Layouts. CoRR abs/2003.07449 (2020) - [i328]Miles Brundage, Shahar Avin, Jasmine Wang, Haydn Belfield, Gretchen Krueger, Gillian K. Hadfield, Heidy Khlaaf, Jingying Yang, Helen Toner, Ruth Fong, Tegan Maharaj, Pang Wei Koh, Sara Hooker, Jade Leung, Andrew Trask, Emma Bluemke, Jonathan Lebensold, Cullen O'Keefe, Mark Koren, Théo Ryffel, J. B. Rubinovitz, Tamay Besiroglu, Federica Carugati, Jack Clark, Peter Eckersley, Sarah de Haas, Maritza Johnson, Ben Laurie, Alex Ingerman, Igor Krawczuk, Amanda Askell, Rosario Cammarota, Andrew Lohn, David Krueger, Charlotte Stix, Peter Henderson, Logan Graham, Carina Prunkl, Bianca Martin, Elizabeth Seger, Noa Zilberman, Seán Ó hÉigeartaigh, Frens Kroeger, Girish Sastry, Rebecca Kagan, Adrian Weller, Brian Tse, Elizabeth Barnes, Allan Dafoe, Paul Scharre, Ariel Herbert-Voss, Martijn Rasser, Shagun Sodhani, Carrick Flynn, Thomas Krendl Gilbert, Lisa Dyer, Saif M. Khan, Yoshua Bengio, Markus Anderljung:
Toward Trustworthy AI Development: Mechanisms for Supporting Verifiable Claims. CoRR abs/2004.07213 (2020) - [i327]Yonatan Bisk, Ari Holtzman, Jesse Thomason, Jacob Andreas, Yoshua Bengio, Joyce Chai, Mirella Lapata, Angeliki Lazaridou, Jonathan May, Aleksandr Nisnevich, Nicolas Pinto, Joseph P. Turian:
Experience Grounds Language. CoRR abs/2004.10151 (2020) - [i326]Anirudh Goyal, Yoshua Bengio, Matthew M. Botvinick, Sergey Levine:
The Variational Bandwidth Bottleneck: Stochastic Evaluation on an Information Budget. CoRR abs/2004.11935 (2020) - [i325]Sai Krishna Gottipati, Boris Sattarov, Sufeng Niu, Yashaswi Pathak, Haoran Wei, Shengchao Liu, Karam M. J. Thomas, Simon Blackburn, Connor W. Coley, Jian Tang, Sarath Chandar, Yoshua Bengio:
Learning To Navigate The Synthetically Accessible Chemical Space Using Reinforcement Learning. CoRR abs/2004.12485 (2020) - [i324]Timo Milbich, Karsten Roth, Homanga Bharadhwaj, Samarth Sinha, Yoshua Bengio, Björn Ommer, Joseph Paul Cohen:
DiVA: Diverse Visual Feature Aggregation for Deep Metric Learning. CoRR abs/2004.13458 (2020) - [i323]Maxence Ernoult, Julie Grollier, Damien Querlioz, Yoshua Bengio, Benjamin Scellier:
Equilibrium Propagation with Continual Weight Updates. CoRR abs/2005.04168 (2020) - [i322]Maxence Ernoult, Julie Grollier, Damien Querlioz, Yoshua Bengio, Benjamin Scellier:
Continual Weight Updates and Convolutional Architectures for Equilibrium Propagation. CoRR abs/2005.04169 (2020) - [i321]Wenyu Du, Zhouhan Lin, Yikang Shen, Timothy J. O'Donnell, Yoshua Bengio, Yue Zhang:
Exploiting Syntactic Structure for Better Language Modeling: A Syntactic Distance Approach. CoRR abs/2005.05864 (2020) - [i320]Iulian Vlad Serban, Varun Gupta, Ekaterina Kochmar, Dung Do Vu, Robert Belfer, Joelle Pineau, Aaron C. Courville, Laurent Charlin, Yoshua Bengio:
A Large-Scale, Open-Domain, Mixed-Interface Dialogue-Based ITS for STEM. CoRR abs/2005.06616 (2020) - [i319]Hannah Alsdurf, Yoshua Bengio, Tristan Deleu, Prateek Gupta, Daphne Ippolito, Richard Janda, Max Jarvie, Tyler Kolody, Sekoul Krastev, Tegan Maharaj, Robert Obryk, Dan Pilat, Valerie Pisano, Benjamin Prud'homme, Meng Qu, Nasim Rahaman, Irina Rish, Jean-Franois Rousseau, Abhinav Sharma, Brooke Struck, Jian Tang, Martin Weiss, Yun William Yu:
COVI White Paper. CoRR abs/2005.08502 (2020) - [i318]Rémi Le Priol, Reza Babanezhad Harikandeh, Yoshua Bengio, Simon Lacoste-Julien:
An Analysis of the Adaptation Speed of Causal Models. CoRR abs/2005.09136 (2020) - [i317]Joseph Paul Cohen, Lan Dao, Paul Morrison, Karsten Roth, Yoshua Bengio, Beiyi Shen, Almas Abbasi, Mahsa Hoshmand-Kochi, Marzyeh Ghassemi, Haifang Li, Tim Q. Duong:
Predicting COVID-19 Pneumonia Severity on Chest X-ray with Deep Learning. CoRR abs/2005.11856 (2020) - [i316]Jack D. Kendall, Ross D. Pantone, Kalpana Manickavasagam, Yoshua Bengio, Benjamin Scellier:
Training End-to-End Analog Neural Networks with Equilibrium Propagation. CoRR abs/2006.01981 (2020) - [i315]Axel Laborieux, Maxence Ernoult, Benjamin Scellier, Yoshua Bengio, Julie Grollier, Damien Querlioz:
Scaling Equilibrium Propagation to Deep ConvNets by Drastically Reducing its Gradient Estimator Bias. CoRR abs/2006.03824 (2020) - [i314]Khurram Javed, Martha White, Yoshua Bengio:
Learning Causal Models Online. CoRR abs/2006.07461 (2020) - [i313]Giancarlo Kerg, Bhargav Kanuparthi, Anirudh Goyal, Kyle Goyette, Yoshua Bengio, Guillaume Lajoie:
Untangling tradeoffs between recurrence and self-attention in neural networks. CoRR abs/2006.09471 (2020) - [i312]Yihe Dong, Will Sawin, Yoshua Bengio:
HNHN: Hypergraph Networks with Hyperedge Neurons. CoRR abs/2006.12278 (2020) - [i311]Matthew Amodio, Rim Assouel, Victor Schmidt, Tristan Sylvain, Smita Krishnaswamy, Yoshua Bengio:
Image-to-image Mapping with Many Domains by Sparse Attribute Transfer. CoRR abs/2006.13291 (2020) - [i310]Bo Li, Yezhen Wang, Tong Che, Shanghang Zhang, Sicheng Zhao, Pengfei Xu, Wei Zhou, Yoshua Bengio, Kurt Keutzer:
Rethinking Distributional Matching Based Domain Adaptation. CoRR abs/2006.13352 (2020) - [i309]Prateek Gupta, Maxime Gasse, Elias B. Khalil, M. Pawan Kumar, Andrea Lodi, Yoshua Bengio:
Hybrid Models for Learning to Branch. CoRR abs/2006.15212 (2020) - [i308]Anirudh Goyal, Alex Lamb, Phanideep Gampa, Philippe Beaudoin, Sergey Levine, Charles Blundell, Yoshua Bengio, Michael Mozer:
Object Files and Schemata: Factorizing Declarative and Procedural Knowledge in Dynamical Systems. CoRR abs/2006.16225 (2020) - [i307]Sarthak Mittal, Alex Lamb, Anirudh Goyal, Vikram Voleti, Murray Shanahan, Guillaume Lajoie, Michael Mozer, Yoshua Bengio:
Learning to Combine Top-Down and Bottom-Up Signals in Recurrent Neural Networks with Attention over Modules. CoRR abs/2006.16981 (2020) - [i306]Nasim Rahaman, Anirudh Goyal, Muhammad Waleed Gondal, Manuel Wuthrich, Stefan Bauer, Yash Sharma, Yoshua Bengio, Bernhard Schölkopf:
S2RMs: Spatially Structured Recurrent Modules. CoRR abs/2007.06533 (2020) - [i305]William Fedus, Prajit Ramachandran, Rishabh Agarwal, Yoshua Bengio, Hugo Larochelle, Mark Rowland, Will Dabney:
Revisiting Fundamentals of Experience Replay. CoRR abs/2007.06700 (2020) - [i304]David Yu-Tung Hui, Maxime Chevalier-Boisvert, Dzmitry Bahdanau, Yoshua Bengio:
BabyAI 1.1. CoRR abs/2007.12770 (2020) - [i303]Yoshua Bengio:
Deriving Differential Target Propagation from Iterating Approximate Inverses. CoRR abs/2007.15139 (2020) - [i302]Lucas Willems, Salem Lahlou, Yoshua Bengio:
Mastering Rate based Curriculum Learning. CoRR abs/2008.06456 (2020) - [i301]Taesup Kim, Sungwoong Kim, Yoshua Bengio:
Visual Concept Reasoning Networks. CoRR abs/2008.11783 (2020) - [i300]Meng Qu, Junkun Chen, Louis-Pascal A. C. Xhonneux, Yoshua Bengio, Jian Tang:
RNNLogic: Learning Logic Rules for Reasoning on Knowledge Graphs. CoRR abs/2010.04029 (2020) - [i299]Ossama Ahmed, Frederik Träuble, Anirudh Goyal, Alexander Neitz, Manuel Wüthrich, Yoshua Bengio, Bernhard Schölkopf, Stefan Bauer:
CausalWorld: A Robotic Manipulation Benchmark for Causal Structure and Transfer Learning. CoRR abs/2010.04296 (2020) - [i298]Alex Lamb, Anirudh Goyal, Agnieszka Slowik, Michael Mozer, Philippe Beaudoin, Yoshua Bengio:
Neural Function Modules with Sparse Arguments: A Dynamic Approach to Integrating Information across Layers. CoRR abs/2010.08012 (2020) - [i297]Tristan Sylvain, Francis Dutil, Tess Berthier, Lisa Di-Jorio, Margaux Luck, R. Devon Hjelm, Yoshua Bengio:
Cross-Modal Information Maximization for Medical Imaging: CMIM. CoRR abs/2010.10593 (2020) - [i296]Rithesh Kumar, Kundan Kumar, Vicki Anand, Yoshua Bengio, Aaron C. Courville:
NU-GAN: High resolution neural upsampling with GAN. CoRR abs/2010.11362 (2020) - [i295]Yoshua Bengio, Prateek Gupta, Tegan Maharaj, Nasim Rahaman, Martin Weiss, Tristan Deleu, Eilif B. Müller, Meng Qu, Victor Schmidt, Pierre-Luc St-Charles, Hannah Alsdurf, Olexa Bilaniuk, David L. Buckeridge, Gaétan Marceau Caron, Pierre Luc Carrier, Joumana Ghosn, Satya Ortiz-Gagne, Chris Pal, Irina Rish, Bernhard Schölkopf, Abhinav Sharma, Jian Tang, Andrew Williams:
Predicting Infectiousness for Proactive Contact Tracing. CoRR abs/2010.12536 (2020) - [i294]Prateek Gupta, Tegan Maharaj, Martin Weiss, Nasim Rahaman, Hannah Alsdurf, Abhinav Sharma, Nanor Minoyan, Soren Harnois-Leblanc, Victor Schmidt, Pierre-Luc St-Charles, Tristan Deleu, Andrew Williams, Akshay Patel, Meng Qu, Olexa Bilaniuk, Gaétan Marceau Caron, Pierre Luc Carrier, Satya Ortiz-Gagné, Marc-Andre Rousseau, David L. Buckeridge, Joumana Ghosn, Yang Zhang, Bernhard Schölkopf, Jian Tang, Irina Rish, Christopher Joseph Pal, Joanna Merckx, Eilif B. Müller, Yoshua Bengio:
COVI-AgentSim: an Agent-based Model for Evaluating Methods of Digital Contact Tracing. CoRR abs/2010.16004 (2020) - [i293]Mohammad Pezeshki, Sékou-Oumar Kaba, Yoshua Bengio, Aaron C. Courville, Doina Precup, Guillaume Lajoie:
Gradient Starvation: A Learning Proclivity in Neural Networks. CoRR abs/2011.09468 (2020) - [i292]Cheng-Hao Liu, Maksym Korablyov, Stanislaw Jastrzebski, Pawel Wlodarczyk-Pruszynski, Yoshua Bengio, Marwin H. S. Segler:
RetroGNN: Approximating Retrosynthesis by Graph Neural Networks for De Novo Drug Design. CoRR abs/2011.13042 (2020) - [i291]Anirudh Goyal, Yoshua Bengio:
Inductive Biases for Deep Learning of Higher-Level Cognition. CoRR abs/2011.15091 (2020) - [i290]Shimaa Baraka, Benjamin Akera, Bibek Aryal, Tenzing Chogyal Sherpa, Finu Shresta, Anthony Ortiz, Kris Sankaran, Juan Lavista Ferres, Mir Matin, Yoshua Bengio:
Machine Learning for Glacier Monitoring in the Hindu Kush Himalaya. CoRR abs/2012.05013 (2020)
2010 – 2019
- 2019
- [j95]Benjamin Scellier, Yoshua Bengio:
Equivalence of Equilibrium Propagation and Recurrent Backpropagation. Neural Comput. 31(2) (2019) - [j94]Li Jing, Çaglar Gülçehre, John Peurifoy, Yichen Shen, Max Tegmark, Marin Soljacic, Yoshua Bengio:
Gated Orthogonal Recurrent Units: On Learning to Forget. Neural Comput. 31(4) (2019) - [j93]Kenji Kawaguchi, Yoshua Bengio:
Depth with nonlinearity creates no bad local minima in ResNets. Neural Networks 118: 167-174 (2019) - [c319]Sarath Chandar, Chinnadhurai Sankar, Eugene Vorontsov, Samira Ebrahimi Kahou, Yoshua Bengio:
Towards Non-Saturating Recurrent Units for Modelling Long-Term Dependencies. AAAI 2019: 3280-3287 - [c318]Vincent François-Lavet, Yoshua Bengio, Doina Precup, Joelle Pineau:
Combined Reinforcement Learning via Abstract Representations. AAAI 2019: 3582-3589 - [c317]Chinnadhurai Sankar, Sandeep Subramanian, Chris Pal, Sarath Chandar, Yoshua Bengio:
Do Neural Dialog Systems Use the Conversation History Effectively? An Empirical Study. ACL (1) 2019: 32-37 - [c316]Alex Lamb, Vikas Verma, Juho Kannala, Yoshua Bengio:
Interpolated Adversarial Training: Achieving Robust Neural Networks Without Sacrificing Too Much Accuracy. AISec@CCS 2019: 95-103 - [c315]Xingdi Yuan, Marc-Alexandre Côté, Jie Fu, Zhouhan Lin, Chris Pal, Yoshua Bengio, Adam Trischler:
Interactive Language Learning by Question Answering. EMNLP/IJCNLP (1) 2019: 2796-2813 - [c314]Jessica A. F. Thompson, Marc Schönwiesner, Yoshua Bengio, Daniel Willett:
How Transferable Are Features in Convolutional Neural Network Acoustic Models across Languages? ICASSP 2019: 2827-2831 - [c313]Sanghyun Yoo, Inchul Song, Yoshua Bengio:
A Highly Adaptive Acoustic Model for Accurate Multi-dialect Speech Recognition. ICASSP 2019: 5716-5720 - [c312]Kyle Kastner, João Felipe Santos, Yoshua Bengio, Aaron C. Courville:
Representation Mixing for TTS Synthesis. ICASSP 2019: 5906-5910 - [c311]Mirco Ravanelli, Titouan Parcollet, Yoshua Bengio:
The Pytorch-kaldi Speech Recognition Toolkit. ICASSP 2019: 6465-6469 - [c310]Md Mahfuzur Rahman Siddiquee, Zongwei Zhou, Nima Tajbakhsh, Ruibin Feng, Michael B. Gotway, Yoshua Bengio, Jianming Liang:
Learning Fixed Points in Generative Adversarial Networks: From Image-to-Image Translation to Disease Detection and Localization. ICCV 2019: 191-200 - [c309]Alaaeldin El-Nouby, Shikhar Sharma, Hannes Schulz, R. Devon Hjelm, Layla El Asri, Samira Ebrahimi Kahou, Yoshua Bengio, Graham W. Taylor:
Tell, Draw, and Repeat: Generating and Modifying Images Based on Continual Linguistic Instruction. ICCV 2019: 10303-10311 - [c308]Maxime Chevalier-Boisvert, Dzmitry Bahdanau, Salem Lahlou, Lucas Willems, Chitwan Saharia, Thien Huu Nguyen, Yoshua Bengio:
BabyAI: A Platform to Study the Sample Efficiency of Grounded Language Learning. ICLR (Poster) 2019 - [c307]Ali Farshchian, Juan Alvaro Gallego, Joseph Paul Cohen, Yoshua Bengio, Lee E. Miller, Sara A. Solla:
Adversarial Domain Adaptation for Stable Brain-Machine Interfaces. ICLR (Poster) 2019 - [c306]Anirudh Goyal, Philemon Brakel, William Fedus, Soumye Singhal, Timothy P. Lillicrap, Sergey Levine, Hugo Larochelle, Yoshua Bengio:
Recall Traces: Backtracking Models for Efficient Reinforcement Learning. ICLR (Poster) 2019 - [c305]Anirudh Goyal, Riashat Islam, Daniel Strouse, Zafarali Ahmed, Hugo Larochelle, Matthew M. Botvinick, Yoshua Bengio, Sergey Levine:
InfoBot: Transfer and Exploration via the Information Bottleneck. ICLR (Poster) 2019 - [c304]R. Devon Hjelm, Alex Fedorov, Samuel Lavoie-Marchildon, Karan Grewal, Philip Bachman, Adam Trischler, Yoshua Bengio:
Learning deep representations by mutual information estimation and maximization. ICLR 2019 - [c303]Stanislaw Jastrzebski, Zachary Kenton, Nicolas Ballas, Asja Fischer, Yoshua Bengio, Amos J. Storkey:
On the Relation Between the Sharpest Directions of DNN Loss and the SGD Step Length. ICLR (Poster) 2019 - [c302]Bhargav Kanuparthi, Devansh Arpit, Giancarlo Kerg, Nan Rosemary Ke, Ioannis Mitliagkas, Yoshua Bengio:
h-detach: Modifying the LSTM Gradient Towards Better Optimization. ICLR (Poster) 2019 - [c301]Nan Rosemary Ke, Amanpreet Singh, Ahmed Touati, Anirudh Goyal, Yoshua Bengio, Devi Parikh, Dhruv Batra:
Modeling the Long Term Future in Model-Based Reinforcement Learning. ICLR (Poster) 2019 - [c300]Titouan Parcollet, Mirco Ravanelli, Mohamed Morchid, Georges Linarès, Chiheb Trabelsi, Renato De Mori, Yoshua Bengio:
Quaternion Recurrent Neural Networks. ICLR (Poster) 2019 - [c299]Alexandre Piché, Valentin Thomas, Cyril Ibrahim, Yoshua Bengio, Chris Pal:
Probabilistic Planning with Sequential Monte Carlo methods. ICLR (Poster) 2019 - [c298]Mariya Toneva, Alessandro Sordoni, Remi Tachet des Combes, Adam Trischler, Yoshua Bengio, Geoffrey J. Gordon:
An Empirical Study of Example Forgetting during Deep Neural Network Learning. ICLR (Poster) 2019 - [c297]Petar Velickovic, William Fedus, William L. Hamilton, Pietro Liò, Yoshua Bengio, R. Devon Hjelm:
Deep Graph Infomax. ICLR (Poster) 2019 - [c296]Zijun Zhang, Ruixiang Zhang, Zongpeng Li, Yoshua Bengio, Liam Paull:
Perceptual Generative Autoencoders. DGS@ICLR 2019 - [c295]Alex Lamb, Jonathan Binas, Anirudh Goyal, Sandeep Subramanian, Ioannis Mitliagkas, Yoshua Bengio, Michael Mozer:
State-Reification Networks: Improving Generalization by Modeling the Distribution of Hidden Representations. ICML 2019: 3622-3631 - [c294]Meng Qu, Yoshua Bengio, Jian Tang:
GMNN: Graph Markov Neural Networks. ICML 2019: 5241-5250 - [c293]Nasim Rahaman, Aristide Baratin, Devansh Arpit, Felix Draxler, Min Lin, Fred A. Hamprecht, Yoshua Bengio, Aaron C. Courville:
On the Spectral Bias of Neural Networks. ICML 2019: 5301-5310 - [c292]Vikas Verma, Alex Lamb, Christopher Beckham, Amir Najafi, Ioannis Mitliagkas, David Lopez-Paz, Yoshua Bengio:
Manifold Mixup: Better Representations by Interpolating Hidden States. ICML 2019: 6438-6447 - [c291]Homanga Bharadhwaj, Zihan Wang, Yoshua Bengio, Liam Paull:
A Data-Efficient Framework for Training and Sim-to-Real Transfer of Navigation Policies. ICRA 2019: 782-788 - [c290]Vikas Verma, Alex Lamb, Juho Kannala, Yoshua Bengio, David Lopez-Paz:
Interpolation Consistency Training for Semi-supervised Learning. IJCAI 2019: 3635-3641 - [c289]Santiago Pascual, Mirco Ravanelli, Joan Serrà, Antonio Bonafonte, Yoshua Bengio:
Learning Problem-Agnostic Speech Representations from Multiple Self-Supervised Tasks. INTERSPEECH 2019: 161-165 - [c288]Loren Lugosch, Mirco Ravanelli, Patrick Ignoto, Vikrant Singh Tomar, Yoshua Bengio:
Speech Model Pre-Training for End-to-End Spoken Language Understanding. INTERSPEECH 2019: 814-818 - [c287]Mirco Ravanelli, Yoshua Bengio:
Learning Speaker Representations with Mutual Information. INTERSPEECH 2019: 1153-1157 - [c286]Saeid Asgari Taghanaki, Mohammad Havaei, Tess Berthier, Francis Dutil, Lisa Di-Jorio, Ghassan Hamarneh, Yoshua Bengio:
InfoMask: Masked Variational Latent Representation to Localize Chest Disease. MICCAI (6) 2019: 739-747 - [c285]Christopher Beckham, Sina Honari, Vikas Verma, Alex Lamb, Farnoosh Ghadiri, R. Devon Hjelm, Yoshua Bengio, Chris Pal:
On Adversarial Mixup Resynthesis. NeurIPS 2019: 4348-4359 - [c284]Maxence Ernoult, Julie Grollier, Damien Querlioz, Yoshua Bengio, Benjamin Scellier:
Updates of Equilibrium Prop Match Gradients of Backprop Through Time in an RNN with Static Input. NeurIPS 2019: 7079-7089 - [c283]Ankesh Anand, Evan Racah, Sherjil Ozair, Yoshua Bengio, Marc-Alexandre Côté, R. Devon Hjelm:
Unsupervised State Representation Learning in Atari. NeurIPS 2019: 8766-8779 - [c282]Devansh Arpit, Víctor Campos, Yoshua Bengio:
How to Initialize your Network? Robust Initialization for WeightNorm & ResNets. NeurIPS 2019: 10900-10909 - [c281]Taesup Kim, Sungjin Ahn, Yoshua Bengio:
Variational Temporal Abstraction. NeurIPS 2019: 11566-11575 - [c280]Rahaf Aljundi, Min Lin, Baptiste Goujaud, Yoshua Bengio:
Gradient based sample selection for online continual learning. NeurIPS 2019: 11816-11825 - [c279]Giancarlo Kerg, Kyle Goyette, Maximilian Puelma Touzel, Gauthier Gidel, Eugene Vorontsov, Yoshua Bengio, Guillaume Lajoie:
Non-normal Recurrent Neural Network (nnRNN): learning long time dependencies while improving expressivity with transient dynamics. NeurIPS 2019: 13591-13601 - [c278]Kundan Kumar, Rithesh Kumar, Thibault de Boissiere, Lucas Gestin, Wei Zhen Teoh, Jose Sotelo, Alexandre de Brébisson, Yoshua Bengio, Aaron C. Courville:
MelGAN: Generative Adversarial Networks for Conditional Waveform Synthesis. NeurIPS 2019: 14881-14892 - [c277]Sherjil Ozair, Corey Lynch, Yoshua Bengio, Aäron van den Oord, Sergey Levine, Pierre Sermanet:
Wasserstein Dependency Measure for Representation Learning. NeurIPS 2019: 15578-15588 - [i289]Devansh Arpit, Yoshua Bengio:
The Benefits of Over-parameterization at Initialization in Deep ReLU Networks. CoRR abs/1901.03611 (2019) - [i288]Rithesh Kumar, Anirudh Goyal, Aaron C. Courville, Yoshua Bengio:
Maximum Entropy Generators for Energy-Based Models. CoRR abs/1901.08508 (2019) - [i287]Anirudh Goyal, Riashat Islam, Daniel Strouse, Zafarali Ahmed, Matthew M. Botvinick, Hugo Larochelle, Sergey Levine, Yoshua Bengio:
InfoBot: Transfer and Exploration via the Information Bottleneck. CoRR abs/1901.10902 (2019) - [i286]Yoshua Bengio, Tristan Deleu, Nasim Rahaman, Nan Rosemary Ke, Sébastien Lachapelle, Olexa Bilaniuk, Anirudh Goyal, Christopher J. Pal:
A Meta-Transfer Objective for Learning to Disentangle Causal Mechanisms. CoRR abs/1901.10912 (2019) - [i285]Sarath Chandar, Chinnadhurai Sankar, Eugene Vorontsov, Samira Ebrahimi Kahou, Yoshua Bengio:
Towards Non-saturating Recurrent Units for Modelling Long-term Dependencies. CoRR abs/1902.06704 (2019) - [i284]William Fedus, Carles Gelada, Yoshua Bengio, Marc G. Bellemare, Hugo Larochelle:
Hyperbolic Discounting and Learning over Multiple Horizons. CoRR abs/1902.06865 (2019) - [i283]Nan Rosemary Ke, Amanpreet Singh, Ahmed Touati, Anirudh Goyal, Yoshua Bengio, Devi Parikh, Dhruv Batra:
Learning Dynamics Model in Reinforcement Learning by Incorporating the Long Term Future. CoRR abs/1903.01599 (2019) - [i282]Vikas Verma, Alex Lamb, Juho Kannala, Yoshua Bengio, David Lopez-Paz:
Interpolation Consistency Training for Semi-Supervised Learning. CoRR abs/1903.03825 (2019) - [i281]Rahaf Aljundi, Min Lin, Baptiste Goujaud, Yoshua Bengio:
Online continual learning with no task boundaries. CoRR abs/1903.08671 (2019) - [i280]Saeid Asgari Taghanaki, Mohammad Havaei, Tess Berthier, Francis Dutil, Lisa Di-Jorio, Ghassan Hamarneh, Yoshua Bengio:
InfoMask: Masked Variational Latent Representation to Localize Chest Disease. CoRR abs/1903.11741 (2019) - [i279]Sherjil Ozair, Corey Lynch, Yoshua Bengio, Aäron van den Oord, Sergey Levine, Pierre Sermanet:
Wasserstein Dependency Measure for Representation Learning. CoRR abs/1903.11780 (2019) - [i278]Misha Benjamin, Paul Gagnon, Negar Rostamzadeh, Chris Pal, Yoshua Bengio, Alex Shee:
Towards Standardization of Data Licenses: The Montreal Data License. CoRR abs/1903.12262 (2019) - [i277]Santiago Pascual, Mirco Ravanelli, Joan Serrà, Antonio Bonafonte, Yoshua Bengio:
Learning Problem-agnostic Speech Representations from Multiple Self-supervised Tasks. CoRR abs/1904.03416 (2019) - [i276]Konrad Zolna, Negar Rostamzadeh, Yoshua Bengio, Sungjin Ahn, Pedro O. Pinheiro:
Reinforced Imitation in Heterogeneous Action Space. CoRR abs/1904.03438 (2019) - [i275]Loren Lugosch, Mirco Ravanelli, Patrick Ignoto, Vikrant Singh Tomar, Yoshua Bengio:
Speech Model Pre-training for End-to-End Spoken Language Understanding. CoRR abs/1904.03670 (2019) - [i274]Becks Simpson, Francis Dutil, Yoshua Bengio, Joseph Paul Cohen:
GradMask: Reduce Overfitting by Regularizing Saliency. CoRR abs/1904.07478 (2019) - [i273]Jake Russin, Jason Jo, Randall C. O'Reilly, Yoshua Bengio:
Compositional generalization in a deep seq2seq model by separating syntax and semantics. CoRR abs/1904.09708 (2019) - [i272]Victor Schmidt, Alexandra Luccioni, S. Karthik Mukkavilli, Narmada Balasooriya, Kris Sankaran, Jennifer T. Chayes, Yoshua Bengio:
Visualizing the Consequences of Climate Change Using Cycle-Consistent Adversarial Networks. CoRR abs/1905.03709 (2019) - [i271]Meng Qu, Yoshua Bengio, Jian Tang:
GMNN: Graph Markov Neural Networks. CoRR abs/1905.06214 (2019) - [i270]Jonathan Binas, Sherjil Ozair, Yoshua Bengio:
The Journey is the Reward: Unsupervised Learning of Influential Trajectories. CoRR abs/1905.09334 (2019) - [i269]Boris N. Oreshkin, Dmitri Carpov, Nicolas Chapados, Yoshua Bengio:
N-BEATS: Neural basis expansion analysis for interpretable time series forecasting. CoRR abs/1905.10437 (2019) - [i268]Alex Lamb, Jonathan Binas, Anirudh Goyal, Sandeep Subramanian, Ioannis Mitliagkas, Denis Kazakov, Yoshua Bengio, Michael C. Mozer:
State-Reification Networks: Improving Generalization by Modeling the Distribution of Hidden Representations. CoRR abs/1905.11382 (2019) - [i267]Giancarlo Kerg, Kyle Goyette, Maximilian Puelma Touzel, Gauthier Gidel, Eugene Vorontsov, Yoshua Bengio, Guillaume Lajoie:
Non-normal Recurrent Neural Network (nnRNN): learning long time dependencies while improving expressivity with transient dynamics. CoRR abs/1905.12080 (2019) - [i266]Ghouthi Boukli Hacene, Carlos Eduardo Rosar Kós Lassance, Vincent Gripon, Matthieu Courbariaux, Yoshua Bengio:
Attention Based Pruning for Shift Networks. CoRR abs/1905.12300 (2019) - [i265]Maxence Ernoult, Julie Grollier, Damien Querlioz, Yoshua Bengio, Benjamin Scellier:
Updates of Equilibrium Prop Match Gradients of Backprop Through Time in an RNN with Static Input. CoRR abs/1905.13633 (2019) - [i264]Chinnadhurai Sankar, Sandeep Subramanian, Christopher J. Pal, Sarath Chandar, Yoshua Bengio:
Do Neural Dialog Systems Use the Conversation History Effectively? An Empirical Study. CoRR abs/1906.01603 (2019) - [i263]Devansh Arpit, Victor Campos, Yoshua Bengio:
How to Initialize your Network? Robust Initialization for WeightNorm & ResNets. CoRR abs/1906.02341 (2019) - [i262]Shagun Sodhani, Anirudh Goyal, Tristan Deleu, Yoshua Bengio, Sergey Levine, Jian Tang:
Learning Powerful Policies by Using Consistent Dynamics Model. CoRR abs/1906.04355 (2019) - [i261]David Rolnick, Priya L. Donti, Lynn H. Kaack, Kelly Kochanski, Alexandre Lacoste, Kris Sankaran, Andrew Slavin Ross, Nikola Milojevic-Dupont, Natasha Jaques, Anna Waldman-Brown, Alexandra Luccioni, Tegan Maharaj, Evan D. Sherwin, S. Karthik Mukkavilli, Konrad P. Körding, Carla P. Gomes, Andrew Y. Ng, Demis Hassabis, John C. Platt, Felix Creutzig, Jennifer T. Chayes, Yoshua Bengio:
Tackling Climate Change with Machine Learning. CoRR abs/1906.05433 (2019) - [i260]Min Lin, Jie Fu, Yoshua Bengio:
Conditional Computation for Continual Learning. CoRR abs/1906.06635 (2019) - [i259]Alex Lamb, Vikas Verma, Juho Kannala, Yoshua Bengio:
Interpolated Adversarial Training: Achieving Robust Neural Networks without Sacrificing Accuracy. CoRR abs/1906.06784 (2019) - [i258]Valentin Thomas, Fabian Pedregosa, Bart van Merriënboer, Pierre-Antoine Manzagol, Yoshua Bengio, Nicolas Le Roux:
Information matrices and generalization. CoRR abs/1906.07774 (2019) - [i257]Ankesh Anand, Evan Racah, Sherjil Ozair, Yoshua Bengio, Marc-Alexandre Côté, R. Devon Hjelm:
Unsupervised State Representation Learning in Atari. CoRR abs/1906.08226 (2019) - [i256]Zijun Zhang, Ruixiang Zhang, Zongpeng Li, Yoshua Bengio, Liam Paull:
Perceptual Generative Autoencoders. CoRR abs/1906.10335 (2019) - [i255]Anirudh Goyal, Shagun Sodhani, Jonathan Binas, Xue Bin Peng, Sergey Levine, Yoshua Bengio:
Reinforcement Learning with Competitive Ensembles of Information-Constrained Primitives. CoRR abs/1906.10667 (2019) - [i254]Nasim Rahaman, Steffen Wolf, Anirudh Goyal, Roman Remme, Yoshua Bengio:
Learning the Arrow of Time. CoRR abs/1907.01285 (2019) - [i253]Meng Qu, Jian Tang, Yoshua Bengio:
Weakly-supervised Knowledge Graph Alignment with Adversarial Learning. CoRR abs/1907.03179 (2019) - [i252]Md Mahfuzur Rahman Siddiquee, Zongwei Zhou, Nima Tajbakhsh, Ruibin Feng, Michael B. Gotway, Yoshua Bengio, Jianming Liang:
Learning Fixed Points in Generative Adversarial Networks: From Image-to-Image Translation to Disease Detection and Localization. CoRR abs/1908.06965 (2019) - [i251]Xingdi Yuan, Marc-Alexandre Côté, Jie Fu, Zhouhan Lin, Christopher J. Pal, Yoshua Bengio, Adam Trischler:
Interactive Language Learning by Question Answering. CoRR abs/1908.10909 (2019) - [i250]Jordan Hoffmann, Louis Maestrati, Yoshihide Sawada, Jian Tang, Jean Michel D. Sellier, Yoshua Bengio:
Data-Driven Approach to Encoding and Decoding 3-D Crystal Structures. CoRR abs/1909.00949 (2019) - [i249]Tristan Deleu, Tobias Würfl, Mandana Samiei, Joseph Paul Cohen, Yoshua Bengio:
Torchmeta: A Meta-Learning library for PyTorch. CoRR abs/1909.06576 (2019) - [i248]Anirudh Goyal, Alex Lamb, Jordan Hoffmann, Shagun Sodhani, Sergey Levine, Yoshua Bengio, Bernhard Schölkopf:
Recurrent Independent Mechanisms. CoRR abs/1909.10893 (2019) - [i247]David Venuto, Léonard Boussioux, Junhao Wang, Rola Dali, Jhelum Chakravorty, Yoshua Bengio, Doina Precup:
Avoidance Learning Using Observational Reinforcement Learning. CoRR abs/1909.11228 (2019) - [i246]Vikas Verma, Meng Qu, Alex Lamb, Yoshua Bengio, Juho Kannala, Jian Tang:
GraphMix: Regularized Training of Graph Neural Networks for Semi-Supervised Learning. CoRR abs/1909.11715 (2019) - [i245]Joseph D. Viviano, Becks Simpson, Francis Dutil, Yoshua Bengio, Joseph Paul Cohen:
Underwhelming Generalization Improvements From Controlling Feature Attribution. CoRR abs/1910.00199 (2019) - [i244]Taesup Kim, Sungjin Ahn, Yoshua Bengio:
Variational Temporal Abstraction. CoRR abs/1910.00775 (2019) - [i243]Nan Rosemary Ke, Olexa Bilaniuk, Anirudh Goyal, Stefan Bauer, Hugo Larochelle, Chris Pal, Yoshua Bengio:
Learning Neural Causal Models from Unknown Interventions. CoRR abs/1910.01075 (2019) - [i242]Kundan Kumar, Rithesh Kumar, Thibault de Boissiere, Lucas Gestin, Wei Zhen Teoh, Jose Sotelo, Alexandre de Brébisson, Yoshua Bengio, Aaron C. Courville:
MelGAN: Generative Adversarial Networks for Conditional Waveform Synthesis. CoRR abs/1910.06711 (2019) - [i241]Yimeng Min, S. Karthik Mukkavilli, Yoshua Bengio:
Predicting ice flow using machine learning. CoRR abs/1910.08922 (2019) - [i240]Shawn Tan, Guillaume Androz, Ahmad Chamseddine, Pierre Fecteau, Aaron C. Courville, Yoshua Bengio, Joseph Paul Cohen:
Icentia11K: An Unsupervised Representation Learning Dataset for Arrhythmia Subtype Discovery. CoRR abs/1910.09570 (2019) - [i239]Sharon Zhou, Alexandra Luccioni, Gautier Cosne, Michael S. Bernstein, Yoshua Bengio:
Establishing an Evaluation Metric to Quantify Climate Change Image Realism. CoRR abs/1910.10143 (2019) - [i238]Samarth Sinha, Han Zhang, Anirudh Goyal, Yoshua Bengio, Hugo Larochelle, Augustus Odena:
Small-GAN: Speeding Up GAN Training Using Core-sets. CoRR abs/1910.13540 (2019) - [i237]Tong Che, Xiaofeng Liu, Site Li, Yubin Ge, Ruixiang Zhang, Caiming Xiong, Yoshua Bengio:
Deep Verifier Networks: Verification of Deep Discriminative Models with Deep Generative Models. CoRR abs/1911.07421 (2019) - [i236]Thomas Mesnard, Gaëtan Vignoud, João Sacramento, Walter Senn, Yoshua Bengio:
Ghost Units Yield Biologically Plausible Backprop in Deep Neural Networks. CoRR abs/1911.08585 (2019) - [i235]Anirudh Srinivasan, Dzmitry Bahdanau, Maxime Chevalier-Boisvert, Yoshua Bengio:
Automated curriculum generation for Policy Gradients from Demonstrations. CoRR abs/1912.00444 (2019) - [i234]Jessenia Gonzalez, Debjani Bhowmick, Cesar Beltran, Kris Sankaran, Yoshua Bengio:
Applying Knowledge Transfer for Water Body Segmentation in Peru. CoRR abs/1912.00957 (2019) - [i233]Jessica A. F. Thompson, Yoshua Bengio, Marc Schönwiesner:
The effect of task and training on intermediate representations in convolutional neural networks revealed with modified RV similarity analysis. CoRR abs/1912.02260 (2019) - [i232]Dzmitry Bahdanau, Harm de Vries, Timothy J. O'Donnell, Shikhar Murty, Philippe Beaudoin, Yoshua Bengio, Aaron C. Courville:
CLOSURE: Assessing Systematic Generalization of CLEVR Models. CoRR abs/1912.05783 (2019) - [i231]ByungIn Yoo, Tristan Sylvain, Yoshua Bengio, Junmo Kim:
Joint Learning of Generative Translator and Classifier for Visually Similar Classes. CoRR abs/1912.06994 (2019) - [i230]Yoshua Bengio, Emma Frejinger, Andrea Lodi, Rahul Patel, Sriram Sankaranarayanan:
A learning-based algorithm to quickly compute good primal solutions for Stochastic Integer Programs. CoRR abs/1912.08112 (2019) - [i229]Alexandra Luccioni, Yoshua Bengio:
On the Morality of Artificial Intelligence. CoRR abs/1912.11945 (2019) - 2018
- [j92]Georgy Derevyanko, Sergei Grudinin, Yoshua Bengio, Guillaume Lamoureux:
Deep convolutional networks for quality assessment of protein folds. Bioinform. 34(23): 4046-4053 (2018) - [j91]Heeyoul Choi, Kyunghyun Cho, Yoshua Bengio:
Fine-grained attention mechanism for neural machine translation. Neurocomputing 284: 171-176 (2018) - [j90]Michal Drozdzal, Gabriel Chartrand, Eugene Vorontsov, Mahsa Shakeri, Lisa Di-Jorio, An Tang, Adriana Romero, Yoshua Bengio, Chris Pal, Samuel Kadoury:
Learning normalized inputs for iterative estimation in medical image segmentation. Medical Image Anal. 44: 1-13 (2018) - [j89]Çaglar Gülçehre, Sarath Chandar, Kyunghyun Cho, Yoshua Bengio:
Dynamic Neural Turing Machine with Continuous and Discrete Addressing Schemes. Neural Comput. 30(4) (2018) - [j88]Xu-Yao Zhang, Fei Yin, Yan-Ming Zhang, Cheng-Lin Liu, Yoshua Bengio:
Drawing and Recognizing Chinese Characters with Recurrent Neural Network. IEEE Trans. Pattern Anal. Mach. Intell. 40(4): 849-862 (2018) - [j87]Mirco Ravanelli, Philemon Brakel, Maurizio Omologo, Yoshua Bengio:
Light Gated Recurrent Units for Speech Recognition. IEEE Trans. Emerg. Top. Comput. Intell. 2(2): 92-102 (2018) - [c276]Li Jing, Çaglar Gülçehre, John Peurifoy, Yichen Shen, Max Tegmark, Marin Soljacic, Yoshua Bengio:
Gated Orthogonal Recurrent Units: On Learning to Forget. AAAI Workshops 2018: 720-726 - [c275]Sandeep Subramanian, Tong Wang, Xingdi Yuan, Saizheng Zhang, Adam Trischler, Yoshua Bengio:
Neural Models for Key Phrase Extraction and Question Generation. QA@ACL 2018: 78-88 - [c274]Yikang Shen, Zhouhan Lin, Athul Paul Jacob, Alessandro Sordoni, Aaron C. Courville, Yoshua Bengio:
Straight to the Tree: Constituency Parsing with Neural Syntactic Distance. ACL (1) 2018: 1171-1180 - [c273]Arantxa Casanova, Guillem Cucurull, Michal Drozdzal, Adriana Romero, Yoshua Bengio:
On the Iterative Refinement of Densely Connected Representation Levels for Semantic Segmentation. CVPR Workshops 2018: 978-987 - [c272]Zhilin Yang, Peng Qi, Saizheng Zhang, Yoshua Bengio, William W. Cohen, Ruslan Salakhutdinov, Christopher D. Manning:
HotpotQA: A Dataset for Diverse, Explainable Multi-hop Question Answering. EMNLP 2018: 2369-2380 - [c271]Stanislaw Jastrzebski, Zachary Kenton, Devansh Arpit, Nicolas Ballas, Asja Fischer, Yoshua Bengio, Amos J. Storkey:
Width of Minima Reached by Stochastic Gradient Descent is Influenced by Learning Rate to Batch Size Ratio. ICANN (3) 2018: 392-402 - [c270]Stylianos Ioannis Mimilakis, Konstantinos Drossos, João Felipe Santos, Gerald Schuller, Tuomas Virtanen, Yoshua Bengio:
Monaural Singing Voice Separation with Skip-Filtering Connections and Recurrent Inference of Time-Frequency Mask. ICASSP 2018: 721-725 - [c269]Inchul Song, Junyoung Chung, Taesup Kim, Yoshua Bengio:
Dynamic Frame Skipping for Fast Speech Recognition in Recurrent Neural Network Based Acoustic Models. ICASSP 2018: 4984-4988 - [c268]Dmitriy Serdyuk, Yongqiang Wang, Christian Fuegen, Anuj Kumar, Baiyang Liu, Yoshua Bengio:
Towards End-to-end Spoken Language Understanding. ICASSP 2018: 5754-5758 - [c267]R. Devon Hjelm, Athul Paul Jacob, Adam Trischler, Gerry Che, Kyunghyun Cho, Yoshua Bengio:
Boundary Seeking GANs. ICLR (Poster) 2018 - [c266]Stanislaw Jastrzebski, Devansh Arpit, Nicolas Ballas, Vikas Verma, Tong Che, Yoshua Bengio:
Residual Connections Encourage Iterative Inference. ICLR (Poster) 2018 - [c265]Stanislaw Jastrzebski, Zachary Kenton, Devansh Arpit, Nicolas Ballas, Asja Fischer, Yoshua Bengio, Amos J. Storkey:
Finding Flatter Minima with SGD. ICLR (Workshop) 2018 - [c264]Samira Ebrahimi Kahou, Vincent Michalski, Adam Atkinson, Ákos Kádár, Adam Trischler, Yoshua Bengio:
FigureQA: An Annotated Figure Dataset for Visual Reasoning. ICLR (Workshop) 2018 - [c263]Chen Ma, Junfeng Wen, Yoshua Bengio:
Universal Successor Representations for Transfer Reinforcement Learning. ICLR (Workshop) 2018 - [c262]Benjamin Scellier, Anirudh Goyal, Jonathan Binas, Thomas Mesnard, Yoshua Bengio:
Extending the Framework of Equilibrium Propagation to General Dynamics. ICLR (Workshop) 2018 - [c261]Dmitriy Serdyuk, Nan Rosemary Ke, Alessandro Sordoni, Adam Trischler, Chris Pal, Yoshua Bengio:
Twin Networks: Matching the Future for Sequence Generation. ICLR (Poster) 2018 - [c260]Shikhar Sharma, Dendi Suhubdy, Vincent Michalski, Samira Ebrahimi Kahou, Yoshua Bengio:
ChatPainter: Improving Text to Image Generation using Dialogue. ICLR (Workshop) 2018 - [c259]Sandeep Subramanian, Adam Trischler, Yoshua Bengio, Christopher J. Pal:
Learning General Purpose Distributed Sentence Representations via Large Scale Multi-task Learning. ICLR (Poster) 2018 - [c258]Chiheb Trabelsi, Olexa Bilaniuk, Ying Zhang, Dmitriy Serdyuk, Sandeep Subramanian, João Felipe Santos, Soroush Mehri, Negar Rostamzadeh, Yoshua Bengio, Christopher J. Pal:
Deep Complex Networks. ICLR (Poster) 2018 - [c257]Petar Velickovic, Guillem Cucurull, Arantxa Casanova, Adriana Romero, Pietro Liò, Yoshua Bengio:
Graph Attention Networks. ICLR (Poster) 2018 - [c256]