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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
- 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) - [c456]Xu Tan, Tao Qin, Jiang Bian, Tie-Yan Liu, Yoshua Bengio:
Regeneration Learning: A Learning Paradigm for Data Generation. AAAI 2024: 22614-22622 - [c455]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 - [c454]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 - [c453]Aniket Rajiv Didolkar, Anirudh Goyal, Yoshua Bengio:
Cycle Consistency Driven Object Discovery. ICLR 2024 - [c452]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 - [c451]Leo Feng, Frederick Tung, Hossein Hajimirsadeghi, Yoshua Bengio, Mohamed Osama Ahmed:
Tree Cross Attention. ICLR 2024 - [c450]Edward J. Hu, Moksh Jain, Eric Elmoznino, Younesse Kaddar, Guillaume Lajoie, Yoshua Bengio, Nikolay Malkin:
Amortizing intractable inference in large language models. ICLR 2024 - [c449]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 - [c448]Minsu Kim, Taeyoung Yun, Emmanuel Bengio, Dinghuai Zhang, Yoshua Bengio, Sungsoo Ahn, Jinkyoo Park:
Local Search GFlowNets. ICLR 2024 - [c447]Amin Mansouri, Jason S. Hartford, Yan Zhang, Yoshua Bengio:
Object centric architectures enable efficient causal representation learning. ICLR 2024 - [c446]Ling Pan, Moksh Jain, Kanika Madan, Yoshua Bengio:
Pre-Training and Fine-Tuning Generative Flow Networks. ICLR 2024 - [c445]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 - [c444]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 - [c443]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 - [c442]Leo Feng, Frederick Tung, Hossein Hajimirsadeghi, Yoshua Bengio, Mohamed Osama Ahmed:
Memory Efficient Neural Processes via Constant Memory Attention Block. ICML 2024 - [c441]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 - [c440]Pablo Lemos, Nikolay Malkin, Will Handley, Yoshua Bengio, Yashar Hezaveh, Laurence Perreault Levasseur:
Improving Gradient-Guided Nested Sampling for Posterior Inference. ICML 2024 - [c439]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 - [i535]Thomas Jiralerspong, Xiaoyin Chen, Yash More, Vedant Shah, Yoshua Bengio:
Efficient Causal Graph Discovery Using Large Language Models. CoRR abs/2402.01207 (2024) - [i534]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) - [i533]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) - [i532]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) - [i531]Tristan Deleu, Padideh Nouri, Nikolay Malkin, Doina Precup, Yoshua Bengio:
Discrete Probabilistic Inference as Control in Multi-path Environments. CoRR abs/2402.10309 (2024) - [i530]Yoshua Bengio, Nikolay Malkin:
Machine learning and information theory concepts towards an AI Mathematician. CoRR abs/2403.04571 (2024) - [i529]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) - [i528]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) - [i527]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) - [i526]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) - [i525]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) - [i524]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 Wing, Joshua B. Tenenbaum:
Towards Guaranteed Safe AI: A Framework for Ensuring Robust and Reliable AI Systems. CoRR abs/2405.06624 (2024) - [i523]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) - [i522]Antoine Bellemare Pépin, François Lespinasse, Philipp Thölke, Yann Harel, Kory Mathewson, Jay A. Olson, Yoshua Bengio, Karim Jerbi:
Divergent Creativity in Humans and Large Language Models. CoRR abs/2405.13012 (2024) - [i521]Leo Feng, Frederick Tung, Hossein Hajimirsadeghi, Mohamed Osama Ahmed, Yoshua Bengio, Greg Mori:
Attention as an RNN. CoRR abs/2405.13956 (2024) - [i520]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) - [i519]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) - [i518]George Ma, Emmanuel Bengio, Yoshua Bengio, Dinghuai Zhang:
Baking Symmetry into GFlowNets. CoRR abs/2406.05426 (2024) - [i517]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) - [i516]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) - [i515]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) - [i514]Anas Krichel, Nikolay Malkin, Salem Lahlou, Yoshua Bengio:
On Generalization for Generative Flow Networks. CoRR abs/2407.03105 (2024) - [i513]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) - [i512]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) - [i511]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) - [i510]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) - [i509]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) - [i508]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) - [i507]Leo Feng, Frederick Tung, Mohamed Osama Ahmed, Yoshua Bengio, Hossein Hajimirsadeghi:
Were RNNs All We Needed? CoRR abs/2410.01201 (2024) - [i506]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) - [i505]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) - [i504]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) - [i503]Michael K. Cohen, Marcus Hutter, Yoshua Bengio, Stuart Russell:
RL, but don't do anything I wouldn't do. CoRR abs/2410.06213 (2024) - [i502]Mingde Zhao, Tristan Sylvain, Doina Precup, Yoshua Bengio:
Identifying and Addressing Delusions for Target-Directed Decision-Making. CoRR abs/2410.07096 (2024) - [i501]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) - [i500]Eric Elmoznino, Thomas Jiralerspong, Yoshua Bengio, Guillaume Lajoie:
A Complexity-Based Theory of Compositionality. CoRR abs/2410.14817 (2024) - [i499]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) - [i498]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) - [i497]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) - [i496]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) - 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]