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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
- 2023
[j116]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)- [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) - [c405]Edoardo Maria Ponti, Alessandro Sordoni, Yoshua Bengio, Siva Reddy:
Combining Parameter-efficient Modules for Task-level Generalisation. EACL 2023: 687-702 - [i448]Xu Tan, Tao Qin, Jiang Bian, Tie-Yan Liu, Yoshua Bengio:
Regeneration Learning: A Learning Paradigm for Data Generation. CoRR abs/2301.08846 (2023) - [i447]Sumukh K. Aithal, Anirudh Goyal, Alex Lamb, Yoshua Bengio, Michael Mozer:
Leveraging the Third Dimension in Contrastive Learning. CoRR abs/2301.11790 (2023) - [i446]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) - [i445]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) - [i444]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) - [i443]Ling Pan, Nikolay Malkin, Dinghuai Zhang, Yoshua Bengio:
Better Training of GFlowNets with Local Credit and Incomplete Trajectories. CoRR abs/2302.01687 (2023) - [i442]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) - [i441]Dinghuai Zhang, Ling Pan, Ricky T. Q. Chen, Aaron C. Courville, Yoshua Bengio:
Distributional GFlowNets with Quantile Flows. CoRR abs/2302.05793 (2023) - [i440]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) - [i439]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) - [i438]Ling Pan, Dinghuai Zhang, Moksh Jain, Longbo Huang, Yoshua Bengio:
Stochastic Generative Flow Networks. CoRR abs/2302.09465 (2023) - [i437]Trang Nguyen, Amin Mansouri, Kanika Madan, Khuong Nguyen, Kartik Ahuja, Dianbo Liu, Yoshua Bengio:
Reusable Slotwise Mechanisms. CoRR abs/2302.10503 (2023) - [i436]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) - [i435]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) - 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. 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 M. 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 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]