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2020 – today
- 2023
[i49]Yilun Du, Mengjiao Yang, Bo Dai, Hanjun Dai, Ofir Nachum, Joshua B. Tenenbaum, Dale Schuurmans, Pieter Abbeel:
Learning Universal Policies via Text-Guided Video Generation. CoRR abs/2302.00111 (2023)- [i48]Ethan Chun, Yilun Du, Anthony Simeonov, Tomás Lozano-Pérez, Leslie Pack Kaelbling:
Local Neural Descriptor Fields: Locally Conditioned Object Representations for Manipulation. CoRR abs/2302.03573 (2023) - [i47]Yilun Du, Conor Durkan, Robin Strudel, Joshua B. Tenenbaum, Sander Dieleman, Rob Fergus, Jascha Sohl-Dickstein, Arnaud Doucet, Will Grathwohl:
Reduce, Reuse, Recycle: Compositional Generation with Energy-Based Diffusion Models and MCMC. CoRR abs/2302.11552 (2023) - [i46]Sherry Yang, Ofir Nachum, Yilun Du, Jason Wei, Pieter Abbeel, Dale Schuurmans:
Foundation Models for Decision Making: Problems, Methods, and Opportunities. CoRR abs/2303.04129 (2023) - [i45]Cheng Chi, Siyuan Feng, Yilun Du, Zhenjia Xu, Eric Cousineau, Benjamin Burchfiel, Shuran Song:
Diffusion Policy: Visuomotor Policy Learning via Action Diffusion. CoRR abs/2303.04137 (2023) - [i44]Jiahui Fu, Yilun Du, Kurran Singh, Joshua B. Tenenbaum, John J. Leonard:
NeuSE: Neural SE(3)-Equivariant Embedding for Consistent Spatial Understanding with Objects. CoRR abs/2303.07308 (2023) - [i43]Yining Hong, Chunru Lin, Yilun Du, Zhenfang Chen, Joshua B. Tenenbaum, Chuang Gan:
3D Concept Learning and Reasoning from Multi-View Images. CoRR abs/2303.11327 (2023) - [i42]Hongyi Chen, Yilun Du, Yiye Chen, Joshua B. Tenenbaum, Patricio A. Vela:
Planning with Sequence Models through Iterative Energy Minimization. CoRR abs/2303.16189 (2023) - [i41]Yilun Du, Cameron Smith, Ayush Tewari, Vincent Sitzmann:
Learning to Render Novel Views from Wide-Baseline Stereo Pairs. CoRR abs/2304.08463 (2023) - [i40]Kevin Black, Michael Janner, Yilun Du, Ilya Kostrikov, Sergey Levine:
Training Diffusion Models with Reinforcement Learning. CoRR abs/2305.13301 (2023) - 2022
- [c37]Shuang Li, Yilun Du, Gido van de Ven, Igor Mordatch:
Energy-Based Models for Continual Learning. CoLLAs 2022: 1-22 - [c36]Rylan Schaeffer, Gabrielle Kaili-May Liu, Yilun Du, Scott Linderman, Ila Rani Fiete:
Streaming Inference for Infinite Non-Stationary Clustering. CoLLAs 2022: 310-326 - [c35]Anthony Simeonov, Yilun Du, Yen-Chen Lin, Alberto Rodriguez Garcia, Leslie Pack Kaelbling, Tomás Lozano-Pérez, Pulkit Agrawal:
SE(3)-Equivariant Relational Rearrangement with Neural Descriptor Fields. CoRL 2022: 835-846 - [c34]Yen-Chen Lin, Pete Florence, Andy Zeng, Jonathan T. Barron, Yilun Du, Wei-Chiu Ma, Anthony Simeonov, Alberto Rodriguez Garcia, Phillip Isola:
MIRA: Mental Imagery for Robotic Affordances. CoRL 2022: 1916-1927 - [c33]Klaus Greff, Francois Belletti, Lucas Beyer, Carl Doersch, Yilun Du, Daniel Duckworth, David J. Fleet, Dan Gnanapragasam, Florian Golemo, Charles Herrmann, Thomas Kipf, Abhijit Kundu, Dmitry Lagun, Issam H. Laradji, Hsueh-Ti Derek Liu, Henning Meyer, Yishu Miao, Derek Nowrouzezahrai, A. Cengiz Öztireli, Etienne Pot, Noha Radwan, Daniel Rebain, Sara Sabour, Mehdi S. M. Sajjadi, Matan Sela, Vincent Sitzmann, Austin Stone, Deqing Sun, Suhani Vora, Ziyu Wang, Tianhao Wu, Kwang Moo Yi, Fangcheng Zhong, Andrea Tagliasacchi:
Kubric: A scalable dataset generator. CVPR 2022: 3739-3751 - [c32]Nan Liu
, Shuang Li, Yilun Du, Antonio Torralba, Joshua B. Tenenbaum:
Compositional Visual Generation with Composable Diffusion Models. ECCV (17) 2022: 423-439 - [c31]Yilun Du, Karim Abed-Meraim, Ouahbi Rekik:
Joint Channel Estimation and MAP Detection of Probabilistically Shaped QAM. EUSIPCO 2022: 1721-1725 - [c30]Yilun Du, Shuang Li, Joshua B. Tenenbaum, Igor Mordatch:
Learning Iterative Reasoning through Energy Minimization. ICML 2022: 5570-5582 - [c29]Michael Janner, Yilun Du, Joshua B. Tenenbaum, Sergey Levine:
Planning with Diffusion for Flexible Behavior Synthesis. ICML 2022: 9902-9915 - [c28]Rylan Schaeffer, Yilun Du, Gabrielle K. Liu, Ila Fiete:
Streaming Inference for Infinite Feature Models. ICML 2022: 19366-19387 - [c27]Anthony Simeonov, Yilun Du, Andrea Tagliasacchi, Joshua B. Tenenbaum, Alberto Rodriguez, Pulkit Agrawal, Vincent Sitzmann:
Neural Descriptor Fields: SE(3)-Equivariant Object Representations for Manipulation. ICRA 2022: 6394-6400 - [c26]Jiahui Fu, Yilun Du, Kurran Singh, Joshua B. Tenenbaum, John J. Leonard:
Robust Change Detection Based on Neural Descriptor Fields. IROS 2022: 2817-2824 - [c25]Yilun Du, Tomás Lozano-Pérez, Leslie Pack Kaelbling:
Learning Object-Based State Estimators for Household Robots. IROS 2022: 12558-12565 - [c24]Yining Hong, Yilun Du, Chunru Lin, Josh Tenenbaum, Chuang Gan:
3D Concept Grounding on Neural Fields. NeurIPS 2022 - [c23]Shuang Li, Xavier Puig, Chris Paxton, Yilun Du, Clinton Wang, Linxi Fan, Tao Chen, De-An Huang, Ekin Akyürek, Anima Anandkumar, Jacob Andreas, Igor Mordatch, Antonio Torralba, Yuke Zhu:
Pre-Trained Language Models for Interactive Decision-Making. NeurIPS 2022 - [c22]Andrew Luo, Yilun Du, Michael J. Tarr, Josh Tenenbaum, Antonio Torralba, Chuang Gan:
Learning Neural Acoustic Fields. NeurIPS 2022 - [i39]Shuang Li, Xavier Puig, Chris Paxton, Yilun Du, Clinton Wang, Linxi Fan, Tao Chen, De-An Huang, Ekin Akyürek, Anima Anandkumar, Jacob Andreas, Igor Mordatch, Antonio Torralba, Yuke Zhu:
Pre-Trained Language Models for Interactive Decision-Making. CoRR abs/2202.01771 (2022) - [i38]Klaus Greff, Francois Belletti, Lucas Beyer, Carl Doersch, Yilun Du, Daniel Duckworth, David J. Fleet, Dan Gnanapragasam, Florian Golemo, Charles Herrmann, Thomas Kipf, Abhijit Kundu, Dmitry Lagun, Issam H. Laradji, Hsueh-Ti Derek Liu, Henning Meyer, Yishu Miao, Derek Nowrouzezahrai, Cengiz Öztireli, Etienne Pot, Noha Radwan, Daniel Rebain, Sara Sabour, Mehdi S. M. Sajjadi, Matan Sela, Vincent Sitzmann, Austin Stone, Deqing Sun, Suhani Vora, Ziyu Wang, Tianhao Wu, Kwang Moo Yi, Fangcheng Zhong, Andrea Tagliasacchi:
Kubric: A scalable dataset generator. CoRR abs/2203.03570 (2022) - [i37]Andrew Luo, Yilun Du, Michael J. Tarr, Joshua B. Tenenbaum, Antonio Torralba, Chuang Gan:
Learning Neural Acoustic Fields. CoRR abs/2204.00628 (2022) - [i36]Rylan Schaeffer, Gabrielle Kaili-May Liu, Yilun Du, Scott Linderman, Ila Rani Fiete:
Streaming Inference for Infinite Non-Stationary Clustering. CoRR abs/2205.01212 (2022) - [i35]Michael Janner, Yilun Du, Joshua B. Tenenbaum, Sergey Levine:
Planning with Diffusion for Flexible Behavior Synthesis. CoRR abs/2205.09991 (2022) - [i34]Nan Liu, Shuang Li, Yilun Du, Antonio Torralba, Joshua B. Tenenbaum:
Compositional Visual Generation with Composable Diffusion Models. CoRR abs/2206.01714 (2022) - [i33]Yilun Du, Shuang Li, Joshua B. Tenenbaum, Igor Mordatch:
Learning Iterative Reasoning through Energy Minimization. CoRR abs/2206.15448 (2022) - [i32]Yining Hong, Yilun Du, Chunru Lin, Joshua B. Tenenbaum, Chuang Gan:
3D Concept Grounding on Neural Fields. CoRR abs/2207.06403 (2022) - [i31]Prafull Sharma, Ayush Tewari, Yilun Du, Sergey Zakharov, Rares Ambrus, Adrien Gaidon, William T. Freeman, Frédo Durand, Joshua B. Tenenbaum, Vincent Sitzmann:
Seeing 3D Objects in a Single Image via Self-Supervised Static-Dynamic Disentanglement. CoRR abs/2207.11232 (2022) - [i30]Jiahui Fu, Yilun Du, Kurran Singh, Joshua B. Tenenbaum, John J. Leonard:
Robust Change Detection Based on Neural Descriptor Fields. CoRR abs/2208.01014 (2022) - [i29]Shuang Li, Yilun Du, Joshua B. Tenenbaum, Antonio Torralba, Igor Mordatch:
Composing Ensembles of Pre-trained Models via Iterative Consensus. CoRR abs/2210.11522 (2022) - [i28]Robin Strudel, Corentin Tallec, Florent Altché, Yilun Du, Yaroslav Ganin, Arthur Mensch, Will Grathwohl, Nikolay Savinov, Sander Dieleman, Laurent Sifre, Rémi Leblond:
Self-conditioned Embedding Diffusion for Text Generation. CoRR abs/2211.04236 (2022) - [i27]Anthony Simeonov, Yilun Du, Yen-Chen Lin, Alberto Rodriguez, Leslie Pack Kaelbling, Tomás Lozano-Pérez, Pulkit Agrawal:
SE(3)-Equivariant Relational Rearrangement with Neural Descriptor Fields. CoRR abs/2211.09786 (2022) - [i26]Anurag Ajay, Yilun Du, Abhi Gupta, Joshua B. Tenenbaum, Tommi S. Jaakkola, Pulkit Agrawal:
Is Conditional Generative Modeling all you need for Decision-Making? CoRR abs/2211.15657 (2022) - [i25]Jose Muguira-Iturralde, Aidan Curtis, Yilun Du, Leslie Pack Kaelbling, Tomás Lozano-Pérez:
Visibility-Aware Navigation Among Movable Obstacles. CoRR abs/2212.02671 (2022) - [i24]Yen-Chen Lin, Pete Florence, Andy Zeng, Jonathan T. Barron, Yilun Du, Wei-Chiu Ma, Anthony Simeonov, Alberto Rodriguez Garcia, Phillip Isola:
MIRA: Mental Imagery for Robotic Affordances. CoRR abs/2212.06088 (2022) - 2021
- [j1]Juan Liu, Yilun Du, Song Shi:
Quark Self-Energy and Condensates in NJL Model with External Magnetic Field. Symmetry 13(8): 1410 (2021) - [c21]Shuang Li, Yilun Du, Antonio Torralba, Josef Sivic, Bryan C. Russell:
Weakly Supervised Human-Object Interaction Detection in Video via Contrastive Spatiotemporal Regions. ICCV 2021: 1825-1835 - [c20]Linqi Zhou, Yilun Du, Jiajun Wu:
3D Shape Generation and Completion through Point-Voxel Diffusion. ICCV 2021: 5806-5815 - [c19]Yilun Du, Chuang Gan, Phillip Isola:
Curious Representation Learning for Embodied Intelligence. ICCV 2021: 10388-10397 - [c18]Yilun Du, Yinan Zhang, Hong-Xing Yu, Joshua B. Tenenbaum, Jiajun Wu:
Neural Radiance Flow for 4D View Synthesis and Video Processing. ICCV 2021: 14304-14314 - [c17]Yilun Du, Kevin A. Smith, Tomer D. Ullman, Joshua B. Tenenbaum, Jiajun Wu:
Unsupervised Discovery of 3D Physical Objects from Video. ICLR 2021 - [c16]Yilun Du, Shuang Li, Joshua B. Tenenbaum, Igor Mordatch:
Improved Contrastive Divergence Training of Energy-Based Models. ICML 2021: 2837-2848 - [c15]Yilun Du, Katie Collins, Josh Tenenbaum, Vincent Sitzmann:
Learning Signal-Agnostic Manifolds of Neural Fields. NeurIPS 2021: 8320-8331 - [c14]Yilun Du, Shuang Li, Yash Sharma, Josh Tenenbaum, Igor Mordatch:
Unsupervised Learning of Compositional Energy Concepts. NeurIPS 2021: 15608-15620 - [c13]Nan Liu, Shuang Li, Yilun Du, Josh Tenenbaum, Antonio Torralba:
Learning to Compose Visual Relations. NeurIPS 2021: 23166-23178 - [c12]Joseph Suarez, Yilun Du, Clare Zhu, Igor Mordatch, Phillip Isola:
The Neural MMO Platform for Massively Multiagent Research. NeurIPS Datasets and Benchmarks 2021 - [i23]Linqi Zhou, Yilun Du, Jiajun Wu:
3D Shape Generation and Completion through Point-Voxel Diffusion. CoRR abs/2104.03670 (2021) - [i22]Yilun Du, Chuang Gan, Phillip Isola:
Curious Representation Learning for Embodied Intelligence. CoRR abs/2105.01060 (2021) - [i21]Shuang Li, Yilun Du, Antonio Torralba, Josef Sivic, Bryan C. Russell:
Weakly Supervised Human-Object Interaction Detection in Video via Contrastive Spatiotemporal Regions. CoRR abs/2110.03562 (2021) - [i20]Joseph Suarez, Yilun Du, Clare Zhu, Igor Mordatch, Phillip Isola:
The Neural MMO Platform for Massively Multiagent Research. CoRR abs/2110.07594 (2021) - [i19]Yilun Du, Shuang Li, Yash Sharma, Joshua B. Tenenbaum, Igor Mordatch:
Unsupervised Learning of Compositional Energy Concepts. CoRR abs/2111.03042 (2021) - [i18]Yilun Du, Katherine M. Collins, Joshua B. Tenenbaum, Vincent Sitzmann:
Learning Signal-Agnostic Manifolds of Neural Fields. CoRR abs/2111.06387 (2021) - [i17]Nan Liu, Shuang Li, Yilun Du, Joshua B. Tenenbaum, Antonio Torralba:
Learning to Compose Visual Relations. CoRR abs/2111.09297 (2021) - [i16]Anthony Simeonov, Yilun Du, Andrea Tagliasacchi, Joshua B. Tenenbaum, Alberto Rodriguez, Pulkit Agrawal, Vincent Sitzmann:
Neural Descriptor Fields: SE(3)-Equivariant Object Representations for Manipulation. CoRR abs/2112.05124 (2021) - 2020
- [c11]Joseph Suarez, Yilun Du, Igor Mordatch, Phillip Isola:
Neural MMO v1.3: A Massively Multiagent Game Environment for Training and Evaluating Neural Networks. AAMAS 2020: 2020-2022 - [c10]Anthony Simeonov, Yilun Du, Beomjoon Kim, Francois Robert Hogan, Joshua B. Tenenbaum, Pulkit Agrawal, Alberto Rodriguez:
A Long Horizon Planning Framework for Manipulating Rigid Pointcloud Objects. CoRL 2020: 1582-1601 - [c9]Yilun Du, Joshua Meier, Jerry Ma, Rob Fergus, Alexander Rives:
Energy-based models for atomic-resolution protein conformations. ICLR 2020 - [c8]Xingyou Song, Yiding Jiang, Stephen Tu, Yilun Du, Behnam Neyshabur:
Observational Overfitting in Reinforcement Learning. ICLR 2020 - [c7]Yilun Du, Shuang Li, Igor Mordatch:
Compositional Visual Generation with Energy Based Models. NeurIPS 2020 - [i15]Joseph Suarez, Yilun Du, Igor Mordatch, Phillip Isola:
Neural MMO v1.3: A Massively Multiagent Game Environment for Training and Evaluating Neural Networks. CoRR abs/2001.12004 (2020) - [i14]Yilun Du, Shuang Li, Igor Mordatch:
Compositional Visual Generation and Inference with Energy Based Models. CoRR abs/2004.06030 (2020) - [i13]Yilun Du, Joshua Meier, Jerry Ma, Rob Fergus, Alexander Rives:
Energy-based models for atomic-resolution protein conformations. CoRR abs/2004.13167 (2020) - [i12]Yilun Du, Kevin Smith, Tomer D. Ullman, Joshua B. Tenenbaum, Jiajun Wu:
Unsupervised Discovery of 3D Physical Objects from Video. CoRR abs/2007.12348 (2020) - [i11]Yilun Du, Joshua B. Tenenbaum, Tomás Lozano-Pérez, Leslie Pack Kaelbling:
Learning Online Data Association. CoRR abs/2011.03183 (2020) - [i10]Anthony Simeonov, Yilun Du, Beomjoon Kim, Francois Robert Hogan, Joshua B. Tenenbaum, Pulkit Agrawal, Alberto Rodriguez:
A Long Horizon Planning Framework for Manipulating Rigid Pointcloud Objects. CoRR abs/2011.08177 (2020) - [i9]Shuang Li, Yilun Du, Gido M. van de Ven, Antonio Torralba, Igor Mordatch:
Energy-Based Models for Continual Learning. CoRR abs/2011.12216 (2020) - [i8]Yilun Du, Shuang Li, Joshua B. Tenenbaum, Igor Mordatch:
Improved Contrastive Divergence Training of Energy Based Models. CoRR abs/2012.01316 (2020) - [i7]Yilun Du, Yinan Zhang, Hong-Xing Yu, Joshua B. Tenenbaum, Jiajun Wu:
Neural Radiance Flow for 4D View Synthesis and Video Processing. CoRR abs/2012.09790 (2020)
2010 – 2019
- 2019
- [c6]Yilun Du, Toru Lin, Igor Mordatch:
Model-Based Planning with Energy-Based Models. CoRL 2019: 374-383 - [c5]Yilun Du, Karthik Narasimhan:
Task-Agnostic Dynamics Priors for Deep Reinforcement Learning. ICML 2019: 1696-1705 - [c4]Yilun Du, Igor Mordatch:
Implicit Generation and Modeling with Energy Based Models. NeurIPS 2019: 3603-3613 - [i6]Joseph Suarez, Yilun Du, Phillip Isola, Igor Mordatch:
Neural MMO: A Massively Multiagent Game Environment for Training and Evaluating Intelligent Agents. CoRR abs/1903.00784 (2019) - [i5]Yilun Du, Igor Mordatch:
Implicit Generation and Generalization in Energy-Based Models. CoRR abs/1903.08689 (2019) - [i4]Yilun Du, Karthik Narasimhan:
Task-Agnostic Dynamics Priors for Deep Reinforcement Learning. CoRR abs/1905.04819 (2019) - [i3]Xingyou Song, Yilun Du, Jacob Jackson:
An Empirical Study on Hyperparameters and their Interdependence for RL Generalization. CoRR abs/1906.00431 (2019) - [i2]Yilun Du, Toru Lin, Igor Mordatch:
Model Based Planning with Energy Based Models. CoRR abs/1909.06878 (2019) - [i1]Xingyou Song, Yiding Jiang, Stephen Tu, Yilun Du, Behnam Neyshabur:
Observational Overfitting in Reinforcement Learning. CoRR abs/1912.02975 (2019) - 2018
- [c3]Yilun Du, Zhijian Liu, Hector Basevi, Ales Leonardis, Bill Freeman, Josh Tenenbaum, Jiajun Wu:
Learning to Exploit Stability for 3D Scene Parsing. NeurIPS 2018: 1733-1743 - 2017
- [c2]Elizabeth Roman, Brian Ulicny, Yilun Du, Srijith Poduval, Allan Ko:
Thomson Reuters' Solution for Triple Ranking in the FEIII 2017 Challenge. DSMM@SIGMOD 2017: 6:1-6:4 - [c1]Elizabeth Roman, Brian Ulicny, Yilun Du, Srijith Poduval, Allan Ko:
Thomson Reuters' Submission to the FEIII 2017 Challenge Non-scored Tasks. DSMM@SIGMOD 2017: 7:1-7:4
Coauthor Index
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