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ORCIDAlán Aspuru-Guzik
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2020 – today
- 2024
[j36]Nicolas Poirier
, Jakob S. Kottmann, Alán Aspuru-Guzik, Luc Mongeau, Alireza Najafi-Yazdi:
Range-separated density functional theory using multiresolution analysis and quantum computing. J. Comput. Chem. 45(23, September): 1987-2000 (2024)- [j35]Nicholas H. Angello, David M. Friday, Changhyun Hwang, Seungjoo Yi, Austin H. Cheng, Tiara Torres-Flores, Edward R. Jira, Wesley Wang, Alán Aspuru-Guzik, Martin D. Burke, Charles M. Schroeder, Ying Diao, Nicholas E. Jackson:
Closed-loop transfer enables artificial intelligence to yield chemical knowledge. Nat. 633(8029): 351-358 (2024) - [j34]Yang Cao, Alán Aspuru-Guzik:
Accelerating discovery in organic redox flow batteries. Nat. Comput. Sci. 4(2): 89-91 (2024) - [c11]Agustinus Kristiadi, Felix Strieth-Kalthoff, Marta Skreta, Pascal Poupart, Alán Aspuru-Guzik, Geoff Pleiss:
A Sober Look at LLMs for Material Discovery: Are They Actually Good for Bayesian Optimization Over Molecules? ICML 2024 - [c10]David Rolnick, Alán Aspuru-Guzik, Sara Beery, Bistra Dilkina, Priya L. Donti, Marzyeh Ghassemi, Hannah Kerner, Claire Monteleoni, Esther Rolf, Milind Tambe, Adam White:
Position: Application-Driven Innovation in Machine Learning. ICML 2024 - [i71]Marta Skreta, Zihan Zhou, Jia Lin Yuan, Kourosh Darvish, Alán Aspuru-Guzik, Animesh Garg:
RePLan: Robotic Replanning with Perception and Language Models. CoRR abs/2401.04157 (2024) - [i70]Kourosh Darvish, Marta Skreta, Yuchi Zhao, Naruki Yoshikawa, Sagnik Som, Miroslav Bogdanovic, Yang Cao, Han Hao, Haoping Xu, Alán Aspuru-Guzik, Animesh Garg, Florian Shkurti:
ORGANA: A Robotic Assistant for Automated Chemistry Experimentation and Characterization. CoRR abs/2401.06949 (2024) - [i69]Philipp Schleich, Lasse Bjørn Kristensen, Jorge A. Campos Gonzalez Angulo, Davide Avagliano, Mohsen Bagherimehrab, Abdulrahman Aldossary, Christoph Gorgulla, Joe Fitzsimons, Alán Aspuru-Guzik:
Chemically Motivated Simulation Problems are Efficiently Solvable by a Quantum Computer. CoRR abs/2401.09268 (2024) - [i68]Agustinus Kristiadi, Felix Strieth-Kalthoff, Marta Skreta, Pascal Poupart, Alán Aspuru-Guzik, Geoff Pleiss:
A Sober Look at LLMs for Material Discovery: Are They Actually Good for Bayesian Optimization Over Molecules? CoRR abs/2402.05015 (2024) - [i67]Mohammad Ghazi Vakili, Christoph Gorgulla, AkshatKumar Nigam, Dmitry Bezrukov, Daniel Varoli, Alex Aliper, Daniil Polykovskiy, Krishna M. Padmanabha Das, Jamie Snider, Anna Lyakisheva, Ardalan Hosseini Mansob, Zhong Yao, Lela Bitar, Eugene Radchenko, Xiao Ding, Jinxin Liu, Fanye Meng, Feng Ren, Yudong Cao, Igor Stagljar, Alán Aspuru-Guzik, Alex Zhavoronkov:
Quantum Computing-Enhanced Algorithm Unveils Novel Inhibitors for KRAS. CoRR abs/2402.08210 (2024) - [i66]Sagi Eppel, Jolina Li, Manuel S. Drehwald, Alán Aspuru-Guzik:
Learning Zero-Shot Material States Segmentation, by Implanting Natural Image Patterns in Synthetic Data. CoRR abs/2403.03309 (2024) - [i65]David Rolnick, Alán Aspuru-Guzik, Sara Beery, Bistra Dilkina, Priya L. Donti, Marzyeh Ghassemi, Hannah Kerner, Claire Monteleoni, Esther Rolf, Milind Tambe, Adam White:
Application-Driven Innovation in Machine Learning. CoRR abs/2403.17381 (2024) - [i64]Haorui Wang, Marta Skreta, Cher-Tian Ser, Wenhao Gao, Lingkai Kong, Felix Streith-Kalthoff, Chenru Duan, Yuchen Zhuang, Yue Yu, Yanqiao Zhu, Yuanqi Du, Alán Aspuru-Guzik, Kirill Neklyudov, Chao Zhang:
Efficient Evolutionary Search Over Chemical Space with Large Language Models. CoRR abs/2406.16976 (2024) - [i63]Zijian Zhang, Sara Aronowitz, Alán Aspuru-Guzik:
A theory of understanding for artificial intelligence: composability, catalysts, and learning. CoRR abs/2408.08463 (2024) - [i62]Austin H. Cheng, Cher Tian Ser, Marta Skreta, Andrés Guzmán-Cordero, Luca A. Thiede, Andreas Burger, Abdulrahman Aldossary, Shi Xuan Leong, Sergio Pablo-García, Felix Strieth-Kalthoff, Alán Aspuru-Guzik:
How to do impactful research in artificial intelligence for chemistry and materials science. CoRR abs/2409.10304 (2024) - 2023
- [j33]Naruki Yoshikawa, Marta Skreta, Kourosh Darvish, Sebastian Arellano-Rubach, Zhi Ji, Lasse Bjørn Kristensen, Andrew Zou Li, Yuchi Zhao, Haoping Xu, Artur Kuramshin, Alán Aspuru-Guzik, Florian Shkurti, Animesh Garg:
Large language models for chemistry robotics. Auton. Robots 47(8): 1057-1086 (2023) - [j32]Po-Yu Kao, Ya-Chu Yang, Wei-Yin Chiang, Jen-Yueh Hsiao, Yudong Cao, Alex Aliper, Feng Ren, Alán Aspuru-Guzik, Alex Zhavoronkov, Min-Hsiu Hsieh, Yen-Chu Lin:
Exploring the Advantages of Quantum Generative Adversarial Networks in Generative Chemistry. J. Chem. Inf. Model. 63(11): 3307-3318 (2023) - [j31]Stanley Lo, Martin Seifrid, Théophile Gaudin, Alán Aspuru-Guzik:
Augmenting Polymer Datasets by Iterative Rearrangement. J. Chem. Inf. Model. 63(14): 4266-4276 (2023) - [j30]Sergio Pablo-García, Santiago Morandi, Rodrigo A. Vargas-Hernández, Kjell Jorner, Zarko Ivkovic, Núria López, Alán Aspuru-Guzik:
Fast evaluation of the adsorption energy of organic molecules on metals via graph neural networks. Nat. Comput. Sci. 3(5): 433-442 (2023) - [c9]Manuel S. Drehwald, Sagi Eppel, Jolina Li, Han Hao, Alán Aspuru-Guzik:
One-shot recognition of any material anywhere using contrastive learning with physics-based rendering. ICCV 2023: 23467-23476 - [c8]Yi Ru Wang, Yuchi Zhao, Haoping Xu, Sagi Eppel, Alán Aspuru-Guzik, Florian Shkurti, Animesh Garg:
MVTrans: Multi-View Perception of Transparent Objects. ICRA 2023: 3771-3778 - [c7]Ryan-Rhys Griffiths, Leo Klarner, Henry B. Moss, Aditya Ravuri, Sang Truong, Yuanqi Du, Samuel Stanton, Gary Tom, Bojana Rankovic, Arian Rokkum Jamasb, Aryan Deshwal, Julius Schwartz, Austin Tripp, Gregory Kell, Simon Frieder, Anthony Bourached, Alex Chan, Jacob Moss, Chengzhi Guo, Johannes Peter Dürholt, Saudamini Chaurasia, Ji Won Park, Felix Strieth-Kalthoff, Alpha A. Lee, Bingqing Cheng, Alán Aspuru-Guzik, Philippe Schwaller, Jian Tang:
GAUCHE: A Library for Gaussian Processes in Chemistry. NeurIPS 2023 - [c6]AkshatKumar Nigam, Robert Pollice, Gary Tom, Kjell Jorner, John Willes, Luca A. Thiede, Anshul Kundaje, Alán Aspuru-Guzik:
Tartarus: A Benchmarking Platform for Realistic And Practical Inverse Molecular Design. NeurIPS 2023 - [i61]Alston Lo, Robert Pollice, AkshatKumar Nigam, Andrew D. White, Mario Krenn, Alán Aspuru-Guzik:
Recent advances in the Self-Referencing Embedding Strings (SELFIES) library. CoRR abs/2302.03620 (2023) - [i60]Yi Ru Wang, Yuchi Zhao, Haoping Xu, Sagi Eppel, Alán Aspuru-Guzik, Florian Shkurti, Animesh Garg:
MVTrans: Multi-View Perception of Transparent Objects. CoRR abs/2302.11683 (2023) - [i59]Marta Skreta, Naruki Yoshikawa, Sebastian Arellano-Rubach, Zhi Ji, Lasse Bjørn Kristensen, Kourosh Darvish, Alán Aspuru-Guzik, Florian Shkurti, Animesh Garg:
Errors are Useful Prompts: Instruction Guided Task Programming with Verifier-Assisted Iterative Prompting. CoRR abs/2303.14100 (2023) - [i58]Daniel Flam-Shepherd, Alán Aspuru-Guzik:
Language models can generate molecules, materials, and protein binding sites directly in three dimensions as XYZ, CIF, and PDB files. CoRR abs/2305.05708 (2023) - [i57]Mohsen Bagherimehrab, Kouhei Nakaji, Nathan Wiebe, Alán Aspuru-Guzik:
Fast quantum algorithm for differential equations. CoRR abs/2306.11802 (2023) - [i56]Xuan Zhang, Limei Wang, Jacob Helwig, Youzhi Luo, Cong Fu, Yaochen Xie, Meng Liu, Yuchao Lin, Zhao Xu, Keqiang Yan, Keir Adams, Maurice Weiler, Xiner Li, Tianfan Fu, Yucheng Wang, Haiyang Yu, Yuqing Xie, Xiang Fu, Alex Strasser, Shenglong Xu, Yi Liu, Yuanqi Du, Alexandra Saxton, Hongyi Ling, Hannah Lawrence, Hannes Stärk, Shurui Gui, Carl Edwards, Nicholas Gao, Adriana Ladera, Tailin Wu, Elyssa F. Hofgard, Aria Mansouri Tehrani, Rui Wang, Ameya Daigavane, Montgomery Bohde, Jerry Kurtin, Qian Huang, Tuong Phung, Minkai Xu, Chaitanya K. Joshi, Simon V. Mathis, Kamyar Azizzadenesheli, Ada Fang, Alán Aspuru-Guzik, Erik J. Bekkers, Michael M. Bronstein, Marinka Zitnik, Anima Anandkumar, Stefano Ermon, Pietro Liò, Rose Yu, Stephan Günnemann, Jure Leskovec, Heng Ji, Jimeng Sun, Regina Barzilay, Tommi S. Jaakkola, Connor W. Coley, Xiaoning Qian, Xiaofeng Qian, Tess E. Smidt, Shuiwang Ji:
Artificial Intelligence for Science in Quantum, Atomistic, and Continuum Systems. CoRR abs/2307.08423 (2023) - [i55]Daniel Flam-Shepherd, Kevin Zhu, Alán Aspuru-Guzik:
Atom-by-atom protein generation and beyond with language models. CoRR abs/2308.09482 (2023) - [i54]Austin H. Cheng, Alston Lo, Santiago Miret, Brooks Pate, Alán Aspuru-Guzik:
Reflection-Equivariant Diffusion for 3D Structure Determination from Isotopologue Rotational Spectra in Natural Abundance. CoRR abs/2310.11609 (2023) - [i53]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) - [i52]Jack Richter-Powell, Luca A. Thiede, Alán Aspuru-Guzik, David Duvenaud:
Sorting Out Quantum Monte Carlo. CoRR abs/2311.05598 (2023) - 2022
- [j29]Devon P. Holst, Pascal Friederich, Alán Aspuru-Guzik, Timothy P. Bender:
Updated Calibrated Model for the Prediction of Molecular Frontier Orbital Energies and Its Application to Boron Subphthalocyanines. J. Chem. Inf. Model. 62(4): 829-840 (2022) - [j28]Luca A. Thiede, Mario Krenn, AkshatKumar Nigam, Alán Aspuru-Guzik:
Curiosity in exploring chemical spaces: intrinsic rewards for molecular reinforcement learning. Mach. Learn. Sci. Technol. 3(3): 35008 (2022) - [j27]Daniel Flam-Shepherd, Tony C. Wu, Xuemei Gu, Alba Cervera-Lierta, Mario Krenn, Alán Aspuru-Guzik:
Learning interpretable representations of entanglement in quantum optics experiments using deep generative models. Nat. Mach. Intell. 4(6): 544-554 (2022) - [j26]Yang Cao, Cher Tian Ser, Marta Skreta, Kjell Jorner, Nathanael Kusanda, Alán Aspuru-Guzik:
Reinforcement learning supercharges redox flow batteries. Nat. Mach. Intell. 4(8): 667-668 (2022) - [j25]Mario Krenn, Qianxiang Ai, Senja Barthel, Nessa Carson, Angelo Frei, Nathan C. Frey, Pascal Friederich, Théophile Gaudin, Alberto Alexander Gayle, Kevin Maik Jablonka, Rafael F. Lameiro, Dominik Lemm, Alston Lo, Seyed Mohamad Moosavi, José Manuel Nápoles-Duarte, AkshatKumar Nigam, Robert Pollice, Kohulan Rajan, Ulrich Schatzschneider, Philippe Schwaller, Marta Skreta, Berend Smit, Felix Strieth-Kalthoff, Chong Sun, Gary Tom, Guido Falk von Rudorff, Andrew Wang, Andrew D. White, Adamo Young, Rose Yu, Alán Aspuru-Guzik:
SELFIES and the future of molecular string representations. Patterns 3(10): 100588 (2022) - [j24]Alba Cervera-Lierta, Mario Krenn, Alán Aspuru-Guzik:
Design of quantum optical experiments with logic artificial intelligence. Quantum 6: 836 (2022) - [i51]Feng Ren, Xiao Ding, Min Zheng, Mikhail Korzinkin, Xin Cai, Wei Zhu, Alexey Mantsyzov, Alex Aliper, Vladimir Aladinskiy, Zhongying Cao, Shanshan Kong, Xi Long, Bonnie Hei Man Liu, Yingtao Liu, Vladimir Naumov, Anastasia Shneyderman, Ivan V. Ozerov, Ju Wang, Frank W. Pun, Alán Aspuru-Guzik, Michael Levitt, Alex Zhavoronkov:
AlphaFold Accelerates Artificial Intelligence Powered Drug Discovery: Efficient Discovery of a Novel Cyclin-dependent Kinase 20 (CDK20) Small Molecule Inhibitor. CoRR abs/2201.09647 (2022) - [i50]Daniel Flam-Shepherd, Alexander Zhigalin, Alán Aspuru-Guzik:
Scalable Fragment-Based 3D Molecular Design with Reinforcement Learning. CoRR abs/2202.00658 (2022) - [i49]Riley J. Hickman, Matteo Aldeghi, Florian Häse, Alán Aspuru-Guzik:
Bayesian optimization with known experimental and design constraints for chemistry applications. CoRR abs/2203.17241 (2022) - [i48]Mario Krenn, Qianxiang Ai, Senja Barthel, Nessa Carson, Angelo Frei, Nathan C. Frey, Pascal Friederich, Théophile Gaudin, Alberto Alexander Gayle, Kevin Maik Jablonka, Rafael F. Lameiro, Dominik Lemm, Alston Lo, Seyed Mohamad Moosavi, José Manuel Nápoles-Duarte, AkshatKumar Nigam, Robert Pollice, Kohulan Rajan, Ulrich Schatzschneider, Philippe Schwaller, Marta Skreta, Berend Smit, Felix Strieth-Kalthoff, Chong Sun, Gary Tom, Guido Falk von Rudorff, Andrew Wang, Andrew D. White, Adamo Young, Rose Yu, Alán Aspuru-Guzik:
SELFIES and the future of molecular string representations. CoRR abs/2204.00056 (2022) - [i47]Mario Krenn, Robert Pollice, Si Yue Guo, Matteo Aldeghi, Alba Cervera-Lierta, Pascal Friederich, Gabriel dos Passos Gomes, Florian Häse, Adrian Jinich, AkshatKumar Nigam, Zhenpeng Yao, Alán Aspuru-Guzik:
On scientific understanding with artificial intelligence. CoRR abs/2204.01467 (2022) - [i46]Abhinav Anand, Jakob S. Kottmann, Alán Aspuru-Guzik:
Quantum compression with classically simulatable circuits. CoRR abs/2207.02961 (2022) - [i45]AkshatKumar Nigam, Robert Pollice, Gary Tom, Kjell Jorner, Luca A. Thiede, Anshul Kundaje, Alán Aspuru-Guzik:
Tartarus: A Benchmarking Platform for Realistic And Practical Inverse Molecular Design. CoRR abs/2209.12487 (2022) - [i44]Zhenpeng Yao, Yanwei Lum, Andrew Johnston, Luis Martin Mejia-Mendoza, Xin Zhou, Yonggang Wen, Alán Aspuru-Guzik, Edward H. Sargent, Zhi Wei Seh:
Machine Learning for a Sustainable Energy Future. CoRR abs/2210.10391 (2022) - [i43]Austin H. Cheng, Andy Cai, Santiago Miret, Gustavo Malkomes, Mariano Phielipp, Alán Aspuru-Guzik:
Group SELFIES: A Robust Fragment-Based Molecular String Representation. CoRR abs/2211.13322 (2022) - [i42]Luca A. Thiede, Chong Sun, Alán Aspuru-Guzik:
Waveflow: Enforcing boundary conditions in smooth normalizing flows with application to fermionic wave functions. CoRR abs/2211.14839 (2022) - [i41]Manuel S. Drehwald, Sagi Eppel, Jolina Li, Han Hao, Alán Aspuru-Guzik:
One-shot recognition of any material anywhere using contrastive learning with physics-based rendering. CoRR abs/2212.00648 (2022) - [i40]Gary Tom, Riley J. Hickman, Aniket Zinzuwadia, Afshan Mohajeri, Benjamín Sánchez-Lengeling, Alán Aspuru-Guzik:
Calibration and generalizability of probabilistic models on low-data chemical datasets with DIONYSUS. CoRR abs/2212.01574 (2022) - [i39]Naruki Yoshikawa, Andrew Zou Li, Kourosh Darvish, Yuchi Zhao, Haoping Xu, Alán Aspuru-Guzik, Animesh Garg, Florian Shkurti:
An Adaptive Robotics Framework for Chemistry Lab Automation. CoRR abs/2212.09672 (2022) - 2021
- [j23]Cyrille Lavigne, Alán Aspuru-Guzik:
funsies: A minimalist, distributed and dynamic workflow engine. J. Open Source Softw. 6(66): 3274 (2021) - [j22]Pascal Friederich, Salvador León, José Darío Perea, Loïc M. Roch, Alán Aspuru-Guzik:
The influence of sorbitol doping on aggregation and electronic properties of PEDOT: PSS: a theoretical study. Mach. Learn. Sci. Technol. 2(1): 01 (2021) - [j21]Pascal Friederich, Mario Krenn, Isaac Tamblyn, Alán Aspuru-Guzik:
Scientific intuition inspired by machine learning-generated hypotheses. Mach. Learn. Sci. Technol. 2(2): 25027 (2021) - [j20]Cynthia Shen, Mario Krenn, Sagi Eppel, Alán Aspuru-Guzik:
Deep molecular dreaming: inverse machine learning for de-novo molecular design and interpretability with surjective representations. Mach. Learn. Sci. Technol. 2(3): 03 (2021) - [j19]Florian Häse, Matteo Aldeghi, Riley J. Hickman, Loïc M. Roch, Melodie Christensen, Elena Liles, Jason E. Hein, Alán Aspuru-Guzik:
Olympus: a benchmarking framework for noisy optimization and experiment planning. Mach. Learn. Sci. Technol. 2(3): 35021 (2021) - [j18]Daniel Flam-Shepherd, Tony C. Wu, Pascal Friederich, Alán Aspuru-Guzik:
Neural message passing on high order paths. Mach. Learn. Sci. Technol. 2(4): 45009 (2021) - [j17]Daniel Flam-Shepherd, Tony C. Wu, Alán Aspuru-Guzik:
MPGVAE: improved generation of small organic molecules using message passing neural nets. Mach. Learn. Sci. Technol. 2(4): 45010 (2021) - [j16]Abhinav Anand, Matthias Degroote, Alán Aspuru-Guzik:
Natural evolutionary strategies for variational quantum computation. Mach. Learn. Sci. Technol. 2(4): 45012 (2021) - [j15]Zhenpeng Yao, Benjamín Sánchez-Lengeling, N. Scott Bobbitt, Benjamin J. Bucior, Sai Govind Hari Kumar, Sean P. Collins, Thomas Burns, Tom K. Woo, Omar K. Farha, Randall Q. Snurr, Alán Aspuru-Guzik:
Inverse design of nanoporous crystalline reticular materials with deep generative models. Nat. Mach. Intell. 3(1): 76-86 (2021) - [c5]Haoping Xu, Yi Ru Wang, Sagi Eppel, Alán Aspuru-Guzik, Florian Shkurti, Animesh Garg:
Seeing Glass: Joint Point-Cloud and Depth Completion for Transparent Objects. CoRL 2021: 827-838 - [i38]Kishor Bharti, Alba Cervera-Lierta, Thi Ha Kyaw, Tobias Haug, Sumner Alperin-Lea, Abhinav Anand, Matthias Degroote, Hermanni Heimonen, Jakob S. Kottmann, Tim Menke, Wai-Keong Mok, Sukin Sim, Leong-Chuan Kwek, Alán Aspuru-Guzik:
Noisy intermediate-scale quantum (NISQ) algorithms. CoRR abs/2101.08448 (2021) - [i37]AkshatKumar Nigam, Robert Pollice, Matthew F. D. Hurley, Riley J. Hickman, Matteo Aldeghi, Naruki Yoshikawa, Seyone Chithrananda, Vincent A. Voelz, Alán Aspuru-Guzik:
Assigning Confidence to Molecular Property Prediction. CoRR abs/2102.11439 (2021) - [i36]Riley J. Hickman, Florian Häse, Loïc M. Roch, Alán Aspuru-Guzik:
Gemini: Dynamic Bias Correction for Autonomous Experimentation and Molecular Simulation. CoRR abs/2103.03391 (2021) - [i35]Matteo Aldeghi, Florian Häse, Riley J. Hickman, Isaac Tamblyn, Alán Aspuru-Guzik:
Golem: An algorithm for robust experiment and process optimization. CoRR abs/2103.03716 (2021) - [i34]Sagi Eppel, Haoping Xu, Alán Aspuru-Guzik:
Computer vision for liquid samples in hospitals and medical labs using hierarchical image segmentation and relations prediction. CoRR abs/2105.01456 (2021) - [i33]AkshatKumar Nigam, Robert Pollice, Alán Aspuru-Guzik:
JANUS: Parallel Tempered Genetic Algorithm Guided by Deep Neural Networks for Inverse Molecular Design. CoRR abs/2106.04011 (2021) - [i32]Daniel Flam-Shepherd, Tony C. Wu, Xuemei Gu, Alba Cervera-Lierta, Mario Krenn, Alán Aspuru-Guzik:
Learning Interpretable Representations of Entanglement in Quantum Optics Experiments using Deep Generative Models. CoRR abs/2109.02490 (2021) - [i31]Sagi Eppel, Haoping Xu, Yi Ru Wang, Alán Aspuru-Guzik:
Predicting 3D shapes, masks, and properties of materials, liquids, and objects inside transparent containers, using the TransProteus CGI dataset. CoRR abs/2109.07577 (2021) - [i30]Alba Cervera-Lierta, Mario Krenn, Alán Aspuru-Guzik:
Design of quantum optical experiments with logic artificial intelligence. CoRR abs/2109.13273 (2021) - [i29]Haoping Xu, Yi Ru Wang, Sagi Eppel, Alán Aspuru-Guzik, Florian Shkurti, Animesh Garg:
Seeing Glass: Joint Point Cloud and Depth Completion for Transparent Objects. CoRR abs/2110.00087 (2021) - [i28]Matthew Choi, Daniel Flam-Shepherd, Thi Ha Kyaw, Alán Aspuru-Guzik:
Learning quantum dynamics with latent neural ODEs. CoRR abs/2110.10721 (2021) - [i27]Daniel Flam-Shepherd, Kevin Zhu, Alán Aspuru-Guzik:
Keeping it Simple: Language Models can learn Complex Molecular Distributions. CoRR abs/2112.03041 (2021) - 2020
- [j14]Ganesh Sivaraman, Nicholas E. Jackson, Benjamín Sánchez-Lengeling, Álvaro Vázquez-Mayagoitia, Alán Aspuru-Guzik, Venkatram Vishwanath, Juan J. de Pablo:
A machine learning workflow for molecular analysis: application to melting points. Mach. Learn. Sci. Technol. 1(2): 25015 (2020) - [j13]Mario Krenn, Florian Häse, AkshatKumar Nigam, Pascal Friederich, Alán Aspuru-Guzik:
Self-referencing embedded strings (SELFIES): A 100% robust molecular string representation. Mach. Learn. Sci. Technol. 1(4): 45024 (2020) - [j12]Ian D. Kivlichan, Craig Gidney, Dominic W. Berry, Nathan Wiebe, Jarrod R. McClean, Wei Sun, Zhang Jiang, Nicholas C. Rubin, Austin G. Fowler, Alán Aspuru-Guzik, Hartmut Neven, Ryan Babbush:
Improved Fault-Tolerant Quantum Simulation of Condensed-Phase Correlated Electrons via Trotterization. Quantum 4: 296 (2020) - [c4]AkshatKumar Nigam, Pascal Friederich, Mario Krenn, Alán Aspuru-Guzik:
Augmenting Genetic Algorithms with Deep Neural Networks for Exploring the Chemical Space. ICLR 2020 - [i26]Daniel Flam-Shepherd, Tony C. Wu, Alán Aspuru-Guzik:
Graph Deconvolutional Generation. CoRR abs/2002.07087 (2020) - [i25]Daniel Flam-Shepherd, Tony C. Wu, Pascal Friederich, Alán Aspuru-Guzik:
Neural Message Passing on High Order Paths. CoRR abs/2002.10413 (2020) - [i24]Florian Häse, Loïc M. Roch, Alán Aspuru-Guzik:
Gryffin: An algorithm for Bayesian optimization for categorical variables informed by physical intuition with applications to chemistry. CoRR abs/2003.12127 (2020) - [i23]Abhinav Anand, Jonathan Romero, Matthias Degroote, Alán Aspuru-Guzik:
Experimental demonstration of a quantum generative adversarial network for continuous distributions. CoRR abs/2006.01976 (2020) - [i22]Florian Häse, Matteo Aldeghi, Riley J. Hickman, Loïc M. Roch, Melodie Christensen, Elena Liles, Jason E. Hein, Alán Aspuru-Guzik:
Olympus: a benchmarking framework for noisy optimization and experiment planning. CoRR abs/2010.04153 (2020) - [i21]Pascal Friederich, Mario Krenn, Isaac Tamblyn, Alán Aspuru-Guzik:
Scientific intuition inspired by machine learning generated hypotheses. CoRR abs/2010.14236 (2020) - [i20]Tony C. Wu, Daniel Flam-Shepherd, Alán Aspuru-Guzik:
Bayesian Variational Optimization for Combinatorial Spaces. CoRR abs/2011.02004 (2020) - [i19]Abhinav Anand, Matthias Degroote, Alán Aspuru-Guzik:
Natural Evolutionary Strategies for Variational Quantum Computation. CoRR abs/2012.00101 (2020) - [i18]Cynthia Shen, Mario Krenn, Sagi Eppel, Alán Aspuru-Guzik:
Deep Molecular Dreaming: Inverse machine learning for de-novo molecular design and interpretability with surjective representations. CoRR abs/2012.09712 (2020) - [i17]Luca A. Thiede, Mario Krenn, AkshatKumar Nigam, Alán Aspuru-Guzik:
Curiosity in exploring chemical space: Intrinsic rewards for deep molecular reinforcement learning. CoRR abs/2012.11293 (2020)
2010 – 2019
- 2019
- [j11]César A. Rodríguez-Rosario, Thomas Frauenheim, Alán Aspuru-Guzik:
Quantum Coherences as a Thermodynamic Potential. Open Syst. Inf. Dyn. 26(4): 1950022:1-1950022:19 (2019) - [i16]Mario Krenn, Florian Häse, AkshatKumar Nigam, Pascal Friederich, Alán Aspuru-Guzik:
SELFIES: a robust representation of semantically constrained graphs with an example application in chemistry. CoRR abs/1905.13741 (2019) - [i15]Lasse Bjørn Kristensen, Matthias Degroote, Peter Wittek, Alán Aspuru-Guzik, Nikolaj Thomas Zinner:
An Artificial Spiking Quantum Neuron. CoRR abs/1907.06269 (2019) - [i14]Sagi Eppel, Alán Aspuru-Guzik:
Generator evaluator-selector net: a modular approach for panoptic segmentation. CoRR abs/1908.09108 (2019) - [i13]AkshatKumar Nigam, Pascal Friederich, Mario Krenn, Alán Aspuru-Guzik:
Augmenting Genetic Algorithms with Deep Neural Networks for Exploring the Chemical Space. CoRR abs/1909.11655 (2019) - [i12]Benjamín Sánchez-Lengeling, Jennifer N. Wei, Brian K. Lee, Richard C. Gerkin, Alán Aspuru-Guzik, Alexander B. Wiltschko:
Machine Learning for Scent: Learning Generalizable Perceptual Representations of Small Molecules. CoRR abs/1910.10685 (2019) - 2018
- [j10]Yudong Cao, Jhonathan Romero, Alán Aspuru-Guzik:
Potential of quantum computing for drug discovery. IBM J. Res. Dev. 62(6): 6:1-6:20 (2018) - [j9]Evgeny Putin, Arip Asadulaev, Yan Ivanenkov, Vladimir Aladinskiy, Benjamín Sánchez-Lengeling, Alán Aspuru-Guzik, Alex Zhavoronkov:
Reinforced Adversarial Neural Computer for de Novo Molecular Design. J. Chem. Inf. Model. 58(6): 1194-1204 (2018) - [j8]Adrian Jinich, Avi I. Flamholz, Haniu Ren, Sungjin Kim, Benjamín Sánchez-Lengeling, Charles A. R. Cotton, Elad Noor, Alán Aspuru-Guzik, Arren Bar-Even:
Quantum chemistry reveals thermodynamic principles of redox biochemistry. PLoS Comput. Biol. 14(10) (2018) - [j7]Florian Häse, Christoph Kreisbeck, Teresa Tamayo-Mendoza, Lars P. E. Yunker, Jason E. Hein, Alán Aspuru-Guzik:
ChemOS: Orchestrating autonomous experimentation. Sci. Robotics 3(19) (2018) - [i11]Daniil Polykovskiy, Alexander Zhebrak, Benjamín Sánchez-Lengeling, Sergey Golovanov, Oktai Tatanov, Stanislav Belyaev, Rauf Kurbanov, Aleksey Artamonov, Vladimir Aladinskiy, Mark Veselov, Artur Kadurin, Sergey I. Nikolenko, Alán Aspuru-Guzik, Alex Zhavoronkov:
Molecular Sets (MOSES): A Benchmarking Platform for Molecular Generation Models. CoRR abs/1811.12823 (2018) - 2017
- [j6]Sungjin Kim, Adrian Jinich, Alán Aspuru-Guzik:
MultiDK: A Multiple Descriptor Multiple Kernel Approach for Molecular Discovery and Its Application to Organic Flow Battery Electrolytes. J. Chem. Inf. Model. 57(4): 657-668 (2017) - [j5]Sarah Mostame, Joonsuk Huh, Christoph Kreisbeck, Andrew J. Kerman, Takatoshi Fujita, Alexander Eisfeld, Alán Aspuru-Guzik:
Emulation of complex open quantum systems using superconducting qubits. Quantum Inf. Process. 16(2): 44 (2017) - [c3]José Miguel Hernández-Lobato, James Requeima, Edward O. Pyzer-Knapp, Alán Aspuru-Guzik:
Parallel and Distributed Thompson Sampling for Large-scale Accelerated Exploration of Chemical Space. ICML 2017: 1470-1479 - [c2]Eric Anschütz, Jonathan Olson, Alán Aspuru-Guzik, Yudong Cao:
Variational Quantum Factoring. QTOP@NetSys 2017: 74-85 - [i10]Gabriel Lima Guimaraes, Benjamín Sánchez-Lengeling, Pedro Luis Cunha Farias, Alán Aspuru-Guzik:
Objective-Reinforced Generative Adversarial Networks (ORGAN) for Sequence Generation Models. CoRR abs/1705.10843 (2017) - [i9]E. Schuyler Fried, Nicolas P. D. Sawaya, Yudong Cao, Ian D. Kivlichan, Jhonathan Romero, Alán Aspuru-Guzik:
qTorch: The Quantum Tensor Contraction Handler. CoRR abs/1709.03636 (2017) - [i8]Yudong Cao, Gian Giacomo Guerreschi, Alán Aspuru-Guzik:
Quantum Neuron: an elementary building block for machine learning on quantum computers. CoRR abs/1711.11240 (2017) - 2016
- [i7]Mikhail Smelyanskiy, Nicolas P. D. Sawaya, Alán Aspuru-Guzik:
qHiPSTER: The Quantum High Performance Software Testing Environment. CoRR abs/1601.07195 (2016) - [i6]Rafael Gómez-Bombarelli, David Duvenaud, José Miguel Hernández-Lobato, Jorge Aguilera-Iparraguirre, Timothy D. Hirzel, Ryan P. Adams, Alán Aspuru-Guzik:
Automatic chemical design using a data-driven continuous representation of molecules. CoRR abs/1610.02415 (2016) - 2015
- [c1]David Duvenaud, Dougal Maclaurin, Jorge Aguilera-Iparraguirre, Rafael Gómez-Bombarelli, Timothy Hirzel, Alán Aspuru-Guzik, Ryan P. Adams:
Convolutional Networks on Graphs for Learning Molecular Fingerprints. NIPS 2015: 2224-2232 - [i5]David Duvenaud, Dougal Maclaurin, Jorge Aguilera-Iparraguirre, Rafael Gómez-Bombarelli, Timothy Hirzel, Alán Aspuru-Guzik, Ryan P. Adams:
Convolutional Networks on Graphs for Learning Molecular Fingerprints. CoRR abs/1509.09292 (2015) - [i4]Salvatore Mandrà, Gian Giacomo Guerreschi, Alán Aspuru-Guzik:
Faster than Classical Quantum Algorithm for dense Formulas of Exact Satisfiability and Occupation Problems. CoRR abs/1512.00859 (2015) - 2014
- [i3]Bryan O'Gorman, Alejandro Perdomo-Ortiz, Ryan Babbush, Alán Aspuru-Guzik, Vadim Smelyanskiy:
Bayesian Network Structure Learning Using Quantum Annealing. CoRR abs/1407.3897 (2014) - 2013
- [i2]James D. Whitfield, Man-Hong Yung, David G. Tempel, Sergio Boixo, Alán Aspuru-Guzik:
Computational complexity of time-dependent density functional theory. CoRR abs/1310.1428 (2013) - 2012
- [i1]James D. Whitfield, Peter J. Love, Alán Aspuru-Guzik:
Computational Complexity in Electronic Structure. CoRR abs/1208.3334 (2012) - 2011
- [j4]Alejandro Perdomo-Ortiz, Salvador E. Venegas-Andraca, Alán Aspuru-Guzik:
A study of heuristic guesses for adiabatic quantum computation. Quantum Inf. Process. 10(1): 33-52 (2011) - 2010
- [j3]Mark Watson, Roberto Olivares-Amaya, Richard G. Edgar, Alán Aspuru-Guzik:
Accelerating Correlated Quantum Chemistry Calculations Using Graphical Processing Units. Comput. Sci. Eng. 12(4): 40-51 (2010)
2000 – 2009
- 2005
- [j2]Alán Aspuru-Guzik, Romelia Salomón-Ferrer, Brian Austin, William A. Lester Jr.:
A sparse algorithm for the evaluation of the local energy in quantum Monte Carlo. J. Comput. Chem. 26(7): 708-715 (2005) - [j1]Alán Aspuru-Guzik, Romelia Salomón-Ferrer, Brian Austin, Raul Perusquía-Flores, Mary A. Griffin, Ricardo A. Oliva, David Skinner, Dominik Domin, William A. Lester Jr.:
Zori 1.0: A parallel quantum Monte Carlo electronic structure package. J. Comput. Chem. 26(8): 856-862 (2005)
Coauthor Index
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