Bengio, Yoshua

468 publications

TMLR 2026 Offline Model-Based Optimization: Comprehensive Review Minsu Kim, Jiayao Gu, Ye Yuan, Taeyoung Yun, Zixuan Liu, Yoshua Bengio, Can Chen
ICLRW 2025 A Physics-Based Data-Driven Model for CO$_2$ Gas Diffusion Electrodes to Drive Automated Laboratories Ivan Grega, Félix Therrien, Abhishek Soni, Karry Ocean, Kevan Dettelbach, Ribwar Ahmadi, Mehrdad Mokhtari, Curtis P. Berlinguette, Yoshua Bengio
ICML 2025 AI for Global Climate Cooperation: Modeling Global Climate Negotiations, Agreements, and Long-Term Cooperation in RICE-N Tianyu Zhang, Andrew Robert Williams, Phillip Wozny, Kai-Hendrik Cohrs, Koen Ponse, Marco Jiralerspong, Soham Rajesh Phade, Sunil Srinivasa, Lu Li, Yang Zhang, Prateek Gupta, Erman Acar, Irina Rish, Yoshua Bengio, Stephan Zheng
ICLR 2025 Action Abstractions for Amortized Sampling Oussama Boussif, Lena Nehale Ezzine, Joseph D Viviano, Michał Koziarski, Moksh Jain, Nikolay Malkin, Emmanuel Bengio, Rim Assouel, Yoshua Bengio
NeurIPS 2025 Adaptive Inference-Time Scaling via Cyclic Diffusion Search Gyubin Lee, Bao N Nguyen Truong, Jaesik Yoon, Dongwoo Lee, Minsu Kim, Yoshua Bengio, Sungjin Ahn
ICLR 2025 Adaptive Teachers for Amortized Samplers Minsu Kim, Sanghyeok Choi, Taeyoung Yun, Emmanuel Bengio, Leo Feng, Jarrid Rector-Brooks, Sungsoo Ahn, Jinkyoo Park, Nikolay Malkin, Yoshua Bengio
NeurIPS 2025 AlignVLM: Bridging Vision and Language Latent Spaces for Multimodal Document Understanding Ahmed Masry, Juan A. Rodriguez, Tianyu Zhang, Suyuchen Wang, Chao Wang, Aarash Feizi, Akshay Kalkunte Suresh, Abhay Puri, Xiangru Jian, Pierre-Andre Noel, Sathwik Tejaswi Madhusudhan, Marco Pedersoli, Bang Liu, Nicolas Chapados, Yoshua Bengio, Enamul Hoque, Christopher Pal, Issam H. Laradji, David Vazquez, Perouz Taslakian, Spandana Gella, Sai Rajeswar
ICLRW 2025 AlignVLM: Bridging Vision and Language Latent Spaces for Multimodal Understanding Ahmed Masry, Juan A. Rodriguez, Tianyu Zhang, Suyuchen Wang, Chao Wang, Aarash Feizi, Akshay Kalkunte Suresh, Abhay Puri, Xiangru Jian, Pierre-Andre Noel, Sathwik Tejaswi Madhusudhan, Marco Pedersoli, Bang Liu, Nicolas Chapados, Yoshua Bengio, Enamul Hoque, Christopher Pal, Issam H. Laradji, David Vazquez, Perouz Taslakian, Spandana Gella, Sai Rajeswar
AISTATS 2025 Ant Colony Sampling with GFlowNets for Combinatorial Optimization Minsu Kim, Sanghyeok Choi, Hyeonah Kim, Jiwoo Son, Jinkyoo Park, Yoshua Bengio
ICLR 2025 AssembleFlow: Rigid Flow Matching with Inertial Frames for Molecular Assembly Hongyu Guo, Yoshua Bengio, Shengchao Liu
ICLR 2025 BigDocs: An Open Dataset for Training Multimodal Models on Document and Code Tasks Juan A. Rodriguez, Xiangru Jian, Siba Smarak Panigrahi, Tianyu Zhang, Aarash Feizi, Abhay Puri, Akshay Kalkunte Suresh, François Savard, Ahmed Masry, Shravan Nayak, Rabiul Awal, Mahsa Massoud, Amirhossein Abaskohi, Zichao Li, Suyuchen Wang, Pierre-Andre Noel, Mats Leon Richter, Saverio Vadacchino, Shubham Agarwal, Sanket Biswas, Sara Shanian, Ying Zhang, Sathwik Tejaswi Madhusudhan, Joao Monteiro, Krishnamurthy Dj Dvijotham, Torsten Scholak, Nicolas Chapados, Sepideh Kharaghani, Sean Hughes, M. Özsu, Siva Reddy, Marco Pedersoli, Yoshua Bengio, Christopher Pal, Issam H. Laradji, Spandana Gella, Perouz Taslakian, David Vazquez, Sai Rajeswar
NeurIPS 2025 Bringing SAM to New Heights: Leveraging Elevation Data for Tree Crown Segmentation from Drone Imagery Mélisande Teng, Arthur Ouaknine, Etienne Laliberté, Yoshua Bengio, David Rolnick, Hugo Larochelle
UAI 2025 Can a Bayesian Oracle Prevent Harm from an Agent? Yoshua Bengio, Michael K. Cohen, Nikolay Malkin, Matt MacDermott, Damiano Fornasiere, Pietro Greiner, Younesse Kaddar
ICLR 2025 Efficient Diversity-Preserving Diffusion Alignment via Gradient-Informed GFlowNets Zhen Liu, Tim Z. Xiao, Weiyang Liu, Yoshua Bengio, Dinghuai Zhang
NeurIPS 2025 Fast Monte Carlo Tree Diffusion: 100× Speedup via Parallel and Sparse Planning Jaesik Yoon, Hyeonseo Cho, Yoshua Bengio, Sungjin Ahn
ICLR 2025 HarmAug: Effective Data Augmentation for Knowledge Distillation of Safety Guard Models Seanie Lee, Haebin Seong, Dong Bok Lee, Minki Kang, Xiaoyin Chen, Dominik Wagner, Yoshua Bengio, Juho Lee, Sung Ju Hwang
ICLRW 2025 Learning Decision Trees as Amortized Structure Inference Mohammed Mahfoud, Ghait Boukachab, Michał Koziarski, Alex Hernández-García, Stefan Bauer, Yoshua Bengio, Nikolay Malkin
ICLR 2025 Learning Diverse Attacks on Large Language Models for Robust Red-Teaming and Safety Tuning Seanie Lee, Minsu Kim, Lynn Cherif, David Dobre, Juho Lee, Sung Ju Hwang, Kenji Kawaguchi, Gauthier Gidel, Yoshua Bengio, Nikolay Malkin, Moksh Jain
TMLR 2025 Low Compute Unlearning via Sparse Representations Vedant Shah, Frederik Träuble, Ashish Malik, Hugo Larochelle, Michael Curtis Mozer, Sanjeev Arora, Yoshua Bengio, Anirudh Goyal
ICLR 2025 MAP: Low-Compute Model Merging with Amortized Pareto Fronts via Quadratic Approximation Lu Li, Tianyu Zhang, Zhiqi Bu, Suyuchen Wang, Huan He, Jie Fu, Yonghui Wu, Jiang Bian, Yong Chen, Yoshua Bengio
ICLR 2025 Meta Flow Matching: Integrating Vector Fields on the Wasserstein Manifold Lazar Atanackovic, Xi Zhang, Brandon Amos, Mathieu Blanchette, Leo J Lee, Yoshua Bengio, Alexander Tong, Kirill Neklyudov
ICLRW 2025 Mitigating Shortcut Learning with Diffusion Counterfactuals and Diverse Ensembles Luca Scimeca, Alexander Rubinstein, Damien Teney, Seong Joon Oh, Yoshua Bengio
ICML 2025 Monte Carlo Tree Diffusion for System 2 Planning Jaesik Yoon, Hyeonseo Cho, Doojin Baek, Yoshua Bengio, Sungjin Ahn
ICLR 2025 On the Transfer of Object-Centric Representation Learning Aniket Rajiv Didolkar, Andrii Zadaianchuk, Anirudh Goyal, Michael Curtis Mozer, Yoshua Bengio, Georg Martius, Maximilian Seitzer
TMLR 2025 Open Problems in Technical AI Governance Anka Reuel, Benjamin Bucknall, Stephen Casper, Timothy 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, Sasha Luccioni, Nitarshan Rajkumar, Nicolas Moës, Jeffrey Ladish, David Bau, Paul Bricman, Neel Guha, Jessica Newman, Yoshua Bengio, Tobin South, Alex Pentland, Sanmi Koyejo, Mykel Kochenderfer, Robert Trager
ICML 2025 Outsourced Diffusion Sampling: Efficient Posterior Inference in Latent Spaces of Generative Models Siddarth Venkatraman, Mohsin Hasan, Minsu Kim, Luca Scimeca, Marcin Sendera, Yoshua Bengio, Glen Berseth, Nikolay Malkin
ICLRW 2025 Outsourced Diffusion Sampling: Efficient Posterior Inference in Latent Spaces of Generative Models Siddarth Venkatraman, Mohsin Hasan, Minsu Kim, Luca Scimeca, Marcin Sendera, Yoshua Bengio, Glen Berseth, Nikolay Malkin
UAI 2025 RL, but Don’t Do Anything I Wouldn’t Do Michael K. Cohen, Marcus Hutter, Yoshua Bengio, Stuart Russell
ICML 2025 Rejecting Hallucinated State Targets During Planning Harry Zhao, Tristan Sylvain, Romain Laroche, Doina Precup, Yoshua Bengio
ICLRW 2025 Shaping Inductive Bias in Diffusion Models Through Frequency-Based Noise Control Thomas Jiralerspong, Berton Earnshaw, Jason Hartford, Yoshua Bengio, Luca Scimeca
ICLRW 2025 Solving Bayesian Inverse Problems with Diffusion Priors and Off-Policy RL Luca Scimeca, Siddarth Venkatraman, Moksh Jain, Minsu Kim, Marcin Sendera, Mohsin Hasan, Alexandre Adam, Yashar Hezaveh, Laurence Perreault-Levasseur, Yoshua Bengio, Glen Berseth, Nikolay Malkin
ICLR 2025 Structure Language Models for Protein Conformation Generation Jiarui Lu, Xiaoyin Chen, Stephen Zhewen Lu, Chence Shi, Hongyu Guo, Yoshua Bengio, Jian Tang
ICLR 2025 Towards Improving Exploration Through Sibling Augmented GFlowNets Kanika Madan, Alex Lamb, Emmanuel Bengio, Glen Berseth, Yoshua Bengio
ICML 2025 Towards a Formal Theory of Representational Compositionality Eric Elmoznino, Thomas Jiralerspong, Yoshua Bengio, Guillaume Lajoie
NeurIPS 2025 Trajectory Balance with Asynchrony: Decoupling Exploration and Learning for Fast, Scalable LLM Post-Training Brian R. Bartoldson, Siddarth Venkatraman, James Diffenderfer, Moksh Jain, Tal Ben-Nun, Seanie Lee, Minsu Kim, Johan Obando-Ceron, Yoshua Bengio, Bhavya Kailkhura
ICLR 2025 VCR: A Task for Pixel-Level Complex Reasoning in Vision Language Models via Restoring Occluded Text Tianyu Zhang, Suyuchen Wang, Lu Li, Ge Zhang, Perouz Taslakian, Sai Rajeswar, Jie Fu, Bang Liu, Yoshua Bengio
NeurIPSW 2024 AI-Assisted Generation of Difficult Math Questions Vedant Shah, Dingli Yu, Kaifeng Lyu, Simon Park, Jiatong Yu, Yinghui He, Nan Rosemary Ke, Michael Curtis Mozer, Yoshua Bengio, Sanjeev Arora, Anirudh Goyal
NeurIPS 2024 Amortizing Intractable Inference in Diffusion Models for Vision, Language, and Control 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
ICLR 2024 Amortizing Intractable Inference in Large Language Models Edward J Hu, Moksh Jain, Eric Elmoznino, Younesse Kaddar, Guillaume Lajoie, Yoshua Bengio, Nikolay Malkin
NeurIPSW 2024 BigDocs: An Open and Permissively-Licensed Dataset for Training Multimodal Models on Document and Code Tasks Juan A. Rodriguez, Xiangru Jian, Siba Smarak Panigrahi, Tianyu Zhang, Aarash Feizi, Abhay Puri, Akshay Kalkunte Suresh, François Savard, Ahmed Masry, Shravan Nayak, Rabiul Awal, Mahsa Massoud, Amirhossein Abaskohi, Zichao Li, Suyuchen Wang, Pierre-Andre Noel, Mats Leon Richter, Saverio Vadacchino, Shubham Agarwal, Sanket Biswas, Sara Shanian, Ying Zhang, Kurt MacDonald, Sathwik Tejaswi Madhusudhan, Joao Monteiro, Krishnamurthy Dj Dvijotham, Torsten Scholak, Nicolas Chapados, Sepideh Kharaghani, Sean Hughes, M. Özsu, Siva Reddy, Marco Pedersoli, Yoshua Bengio, Christopher Pal, Issam H. Laradji, Spandana Gella, Perouz Taslakian, David Vazquez, Sai Rajeswar
NeurIPSW 2024 Can Safety Fine-Tuning Be More Principled? Lessons Learned from Cybersecurity David Williams-King, Linh Le, Adam Oberman, Yoshua Bengio
ICMLW 2024 Cell Morphology-Guided Small Molecule Generation with GFlowNets Stephen Zhewen Lu, Ziqing Lu, Ehsan Hajiramezanali, Tommaso Biancalani, Yoshua Bengio, Gabriele Scalia, Michał Koziarski
ICMLW 2024 Cell Morphology-Guided Small Molecule Generation with GFlowNets Stephen Zhewen Lu, Ziqing Lu, Ehsan Hajiramezanali, Tommaso Biancalani, Yoshua Bengio, Gabriele Scalia, Michał Koziarski
ICMLW 2024 Cell Morphology-Guided Small Molecule Generation with GFlowNets Stephen Zhewen Lu, Ziqing Lu, Ehsan Hajiramezanali, Tommaso Biancalani, Yoshua Bengio, Gabriele Scalia, Michał Koziarski
ICLR 2024 Consciousness-Inspired Spatio-Temporal Abstractions for Better Generalization in Reinforcement Learning Harry Zhao, Safa Alver, Harm van Seijen, Romain Laroche, Doina Precup, Yoshua Bengio
NeurIPSW 2024 Consciousness-Inspired Spatio-Temporal Abstractions for Better Generalization in Reinforcement Learning Harry Zhao, Safa Alver, Harm van Seijen, Romain Laroche, Doina Precup, Yoshua Bengio
ICLR 2024 Cycle Consistency Driven Object Discovery Aniket Rajiv Didolkar, Anirudh Goyal, Yoshua Bengio
ICLR 2024 Delta-AI: Local Objectives for Amortized Inference in Sparse Graphical Models Jean-Pierre René Falet, Hae Beom Lee, Nikolay Malkin, Chen Sun, Dragos Secrieru, Dinghuai Zhang, Guillaume Lajoie, Yoshua Bengio
ICLR 2024 Diffusion Generative Flow Samplers: Improving Learning Signals Through Partial Trajectory Optimization Dinghuai Zhang, Ricky T. Q. Chen, Cheng-Hao Liu, Aaron Courville, Yoshua Bengio
UAI 2024 Discrete Probabilistic Inference as Control in Multi-Path Environments Tristan Deleu, Padideh Nouri, Nikolay Malkin, Doina Precup, Yoshua Bengio
TMLR 2024 Distributional GFlowNets with Quantile Flows Dinghuai Zhang, Ling Pan, Ricky T. Q. Chen, Aaron Courville, Yoshua Bengio
ICLRW 2024 Efficient Causal Graph Discovery Using Large Language Models Thomas Jiralerspong, Xiaoyin Chen, Yash More, Vedant Shah, Yoshua Bengio
ICLR 2024 Expected Flow Networks in Stochastic Environments and Two-Player Zero-Sum Games Marco Jiralerspong, Bilun Sun, Danilo Vucetic, Tianyu Zhang, Yoshua Bengio, Gauthier Gidel, Nikolay Malkin
TMLR 2024 Foundational Challenges in Assuring Alignment and Safety of Large Language Models 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, Jose Hernandez-Orallo, Lewis Hammond, Eric J Bigelow, Alexander Pan, Lauro Langosco, Tomasz Korbak, Heidi Chenyu Zhang, Ruiqi Zhong, Sean O hEigeartaigh, Gabriel Recchia, Giulio Corsi, Alan Chan, Markus Anderljung, Lilian Edwards, Aleksandar Petrov, Christian Schroeder de Witt, Sumeet Ramesh Motwani, Yoshua Bengio, Danqi Chen, Philip Torr, Samuel Albanie, Tegan Maharaj, Jakob Nicolaus Foerster, Florian Tramèr, He He, Atoosa Kasirzadeh, Yejin Choi, David Krueger
NeurIPSW 2024 Identifying and Addressing Delusions for Target-Directed Decision Making Harry Zhao, Tristan Sylvain, Doina Precup, Yoshua Bengio
NeurIPS 2024 Improved Off-Policy Training of Diffusion Samplers Marcin Sendera, Minsu Kim, Sarthak Mittal, Pablo Lemos, Luca Scimeca, Jarrid Rector-Brooks, Alexandre Adam, Yoshua Bengio, Nikolay Malkin
ICML 2024 Improving Gradient-Guided Nested Sampling for Posterior Inference Pablo Lemos, Nikolay Malkin, Will Handley, Yoshua Bengio, Yashar Hezaveh, Laurence Perreault-Levasseur
TMLR 2024 Improving and Generalizing Flow-Based Generative Models with Minibatch Optimal Transport Alexander Tong, Kilian Fatras, Nikolay Malkin, Guillaume Huguet, Yanlei Zhang, Jarrid Rector-Brooks, Guy Wolf, Yoshua Bengio
ICML 2024 Iterated Denoising Energy Matching for Sampling from Boltzmann Densities Tara Akhound-Sadegh, Jarrid Rector-Brooks, Joey Bose, Sarthak Mittal, Pablo Lemos, Cheng-Hao Liu, Marcin Sendera, Siamak Ravanbakhsh, Gauthier Gidel, Yoshua Bengio, Nikolay Malkin, Alexander Tong
NeurIPSW 2024 Learning Diverse Attacks on Large Language Models for Robust Red-Teaming and Safety Tuning Seanie Lee, Minsu Kim, Lynn Cherif, David Dobre, Juho Lee, Sung Ju Hwang, Kenji Kawaguchi, Gauthier Gidel, Yoshua Bengio, Nikolay Malkin, Moksh Jain
ICML 2024 Learning to Scale Logits for Temperature-Conditional GFlowNets Minsu Kim, Joohwan Ko, Taeyoung Yun, Dinghuai Zhang, Ling Pan, Woo Chang Kim, Jinkyoo Park, Emmanuel Bengio, Yoshua Bengio
ICLR 2024 Local Search GFlowNets Minsu Kim, Taeyoung Yun, Emmanuel Bengio, Dinghuai Zhang, Yoshua Bengio, Sungsoo Ahn, Jinkyoo Park
NeurIPSW 2024 MAP: Model Merging with Amortized Pareto Front Using Limited Computation Lu Li, Tianyu Zhang, Zhiqi Bu, Suyuchen Wang, Huan He, Jie Fu, Yonghui Wu, Jiang Bian, Yong Chen, Yoshua Bengio
ICML 2024 Memory Efficient Neural Processes via Constant Memory Attention Block Leo Feng, Frederick Tung, Hossein Hajimirsadeghi, Yoshua Bengio, Mohamed Osama Ahmed
ICMLW 2024 Meta Flow Matching: Integrating Vector Fields on the Wasserstein Manifold Lazar Atanackovic, Xi Zhang, Brandon Amos, Mathieu Blanchette, Leo J Lee, Yoshua Bengio, Alexander Tong, Kirill Neklyudov
NeurIPS 2024 Metacognitive Capabilities of LLMs: An Exploration in Mathematical Problem Solving Aniket Didolkar, Anirudh Goyal, Nan Rosemary Ke, Siyuan Guo, Michal Valko, Timothy Lillicrap, Danilo Rezende, Yoshua Bengio, Michael Mozer, Sanjeev Arora
ICMLW 2024 Metacognitive Capabilities of LLMs: An Exploration in Mathematical Problem Solving Aniket Rajiv Didolkar, Anirudh Goyal, Nan Rosemary Ke, Siyuan Guo, Michal Valko, Timothy P Lillicrap, Danilo Jimenez Rezende, Yoshua Bengio, Michael Curtis Mozer, Sanjeev Arora
TMLR 2024 Multi-Fidelity Active Learning with GFlowNets Alex Hernández-García, Nikita Saxena, Moksh Jain, Cheng-Hao Liu, Yoshua Bengio
ICLR 2024 Object Centric Architectures Enable Efficient Causal Representation Learning Amin Mansouri, Jason Hartford, Yan Zhang, Yoshua Bengio
NeurIPSW 2024 Object-Centric Temporal Consistency via Conditional Autoregressive Inductive Biases Cristian Meo, Akihiro Nakano, Mircea Tudor Lică, Aniket Rajiv Didolkar, Masahiro Suzuki, Anirudh Goyal, Mengmi Zhang, Justin Dauwels, Yutaka Matsuo, Yoshua Bengio
JMLR 2024 PhAST: Physics-Aware, Scalable, and Task-Specific GNNs for Accelerated Catalyst Design Alexandre Duval, Victor Schmidt, Santiago Miret, Yoshua Bengio, Alex Hernández-García, David Rolnick
ICLR 2024 PhyloGFN: Phylogenetic Inference with Generative Flow Networks Ming Yang Zhou, Zichao Yan, Elliot Layne, Nikolay Malkin, Dinghuai Zhang, Moksh Jain, Mathieu Blanchette, Yoshua Bengio
ICLR 2024 Pre-Training and Fine-Tuning Generative Flow Networks Ling Pan, Moksh Jain, Kanika Madan, Yoshua Bengio
NeurIPS 2024 RGFN: Synthesizable Molecular Generation Using GFlowNets Michał Koziarski, Andrei Rekesh, Dmytro Shevchuk, Almer van der Sloot, Piotr Gaiński, Yoshua Bengio, Cheng-Hao Liu, Mike Tyers, Robert A. Batey
ICMLW 2024 RGFN: Synthesizable Molecular Generation Using GFlowNets Michał Koziarski, Andrei Rekesh, Dmytro Shevchuk, Almer M. van der Sloot, Piotr Gaiński, Yoshua Bengio, Cheng-Hao Liu, Mike Tyers, Robert A. Batey
AAAI 2024 Regeneration Learning: A Learning Paradigm for Data Generation Xu Tan, Tao Qin, Jiang Bian, Tie-Yan Liu, Yoshua Bengio
AISTATS 2024 Simulation-Free Schrödinger Bridges via Score and Flow Matching Alexander Y. Tong, Nikolay Malkin, Kilian Fatras, Lazar Atanackovic, Yanlei Zhang, Guillaume Huguet, Guy Wolf, Yoshua Bengio
NeurIPSW 2024 Structure Language Models for Protein Conformation Generation Jiarui Lu, Xiaoyin Chen, Stephen Zhewen Lu, Chence Shi, Hongyu Guo, Yoshua Bengio, Jian Tang
ICLRW 2024 Towards DNA-Encoded Library Generation with GFlowNets Michał Koziarski, Mohammed Abukalam, Vedant Shah, Louis Vaillancourt, Doris Alexandra Schuetz, Moksh Jain, Almer M. van der Sloot, Mathieu Bourgey, Anne Marinier, Yoshua Bengio
NeurIPS 2024 Trajectory Flow Matching with Applications to Clinical Time Series Modelling Xi Zhang, Yuan Pu, Yuki Kawamura, Andrew Loza, Yoshua Bengio, Dennis L. Shung, Alexander Tong
ICLR 2024 Tree Cross Attention Leo Feng, Frederick Tung, Hossein Hajimirsadeghi, Yoshua Bengio, Mohamed Osama Ahmed
NeurIPSW 2024 VCR: Visual Caption Restoration Tianyu Zhang, Suyuchen Wang, Lu Li, Ge Zhang, Perouz Taslakian, Sai Rajeswar, Jie Fu, Bang Liu, Yoshua Bengio
ICML 2023 A Theory of Continuous Generative Flow Networks Salem Lahlou, Tristan Deleu, Pablo Lemos, Dinghuai Zhang, Alexandra Volokhova, Alex Hernández-Garcı́a, Lena Nehale Ezzine, Yoshua Bengio, Nikolay Malkin
AAAI 2023 Adaptive Discrete Communication Bottlenecks with Dynamic Vector Quantization for Heterogeneous Representational Coarseness Dianbo Liu, Alex Lamb, Xu Ji, Pascal Tikeng Notsawo Jr., Michael Mozer, Yoshua Bengio, Kenji Kawaguchi
NeurIPSW 2023 Attention Schema in Neural Agents Dianbo Liu, Samuele Bolotta, Mike He Zhu, Zahra Sheikhbahaee, Yoshua Bengio, Guillaume Dumas
NeurIPSW 2023 Baking Symmetry into GFlowNets George Ma, Emmanuel Bengio, Yoshua Bengio, Dinghuai Zhang
ICMLW 2023 BatchGFN: Generative Flow Networks for Batch Active Learning Shreshth A Malik, Salem Lahlou, Andrew Jesson, Moksh Jain, Nikolay Malkin, Tristan Deleu, Yoshua Bengio, Yarin Gal
ICMLW 2023 Benchmarking Bayesian Causal Discovery Methods for Downstream Treatment Effect Estimation Chris Chinenye Emezue, Alexandre Drouin, Tristan Deleu, Stefan Bauer, Yoshua Bengio
JMLR 2023 Benchmarking Graph Neural Networks Vijay Prakash Dwivedi, Chaitanya K. Joshi, Anh Tuan Luu, Thomas Laurent, Yoshua Bengio, Xavier Bresson
ICML 2023 Better Training of GFlowNets with Local Credit and Incomplete Trajectories Ling Pan, Nikolay Malkin, Dinghuai Zhang, Yoshua Bengio
NeurIPSW 2023 Causal Discovery in Gene Regulatory Networks with GFlowNet: Towards Scalability in Large Systems Trang Nguyen, Alexander Tong, Kanika Madan, Yoshua Bengio, Dianbo Liu
ICMLW 2023 Constant Memory Attention Block Leo Feng, Frederick Tung, Hossein Hajimirsadeghi, Yoshua Bengio, Mohamed Osama Ahmed
NeurIPS 2023 Contrastive Retrospection: Honing in on Critical Steps for Rapid Learning and Generalization in RL Chen Sun, Wannan Yang, Thomas Jiralerspong, Dane Malenfant, Benjamin Alsbury-Nealy, Yoshua Bengio, Blake Richards
NeurIPSW 2023 Crystal-GFN: Sampling Materials with Desirable Properties and Constraints Mistal, Alex Hernández-García, Alexandra Volokhova, Alexandre AGM Duval, Yoshua Bengio, Divya Sharma, Pierre Luc Carrier, Michał Koziarski, Victor Schmidt
TMLR 2023 DEUP: Direct Epistemic Uncertainty Prediction Salem Lahlou, Moksh Jain, Hadi Nekoei, Victor I Butoi, Paul Bertin, Jarrid Rector-Brooks, Maksym Korablyov, Yoshua Bengio
ICML 2023 Discrete Key-Value Bottleneck Frederik Träuble, Anirudh Goyal, Nasim Rahaman, Michael Curtis Mozer, Kenji Kawaguchi, Yoshua Bengio, Bernhard Schölkopf
NeurIPSW 2023 Discrete, Compositional, and Symbolic Representations Through Attractor Dynamics Andrew Joohun Nam, Eric Elmoznino, Nikolay Malkin, Chen Sun, Yoshua Bengio, Guillaume Lajoie
NeurIPS 2023 DynGFN: Towards Bayesian Inference of Gene Regulatory Networks with GFlowNets Lazar Atanackovic, Alexander Tong, Bo Wang, Leo J Lee, Yoshua Bengio, Jason S Hartford
ICML 2023 Equivariance with Learned Canonicalization Functions Sékou-Oumar Kaba, Arnab Kumar Mondal, Yan Zhang, Yoshua Bengio, Siamak Ravanbakhsh
ICML 2023 FAENet: Frame Averaging Equivariant GNN for Materials Modeling Alexandre Agm Duval, Victor Schmidt, Alex Hernández-Garcı́a, Santiago Miret, Fragkiskos D. Malliaros, Yoshua Bengio, David Rolnick
NeurIPS 2023 GEO-Bench: Toward Foundation Models for Earth Monitoring Alexandre Lacoste, Nils Lehmann, Pau Rodriguez, Evan Sherwin, Hannah Kerner, Björn Lütjens, Jeremy Irvin, David Dao, Hamed Alemohammad, Alexandre Drouin, Mehmet Gunturkun, Gabriel Huang, David Vazquez, Dava Newman, Yoshua Bengio, Stefano Ermon, Xiaoxiang Zhu
JMLR 2023 GFlowNet Foundations Yoshua Bengio, Salem Lahlou, Tristan Deleu, Edward J. Hu, Mo Tiwari, Emmanuel Bengio
ICML 2023 GFlowNet-EM for Learning Compositional Latent Variable Models Edward J Hu, Nikolay Malkin, Moksh Jain, Katie E Everett, Alexandros Graikos, Yoshua Bengio
ICLR 2023 GFlowNets and Variational Inference Nikolay Malkin, Salem Lahlou, Tristan Deleu, Xu Ji, Edward J Hu, Katie E Everett, Dinghuai Zhang, Yoshua Bengio
ICMLW 2023 GFlowNets for Causal Discovery: An Overview Dragos Cristian Manta, Edward J Hu, Yoshua Bengio
ICMLW 2023 GFlowNets for Causal Discovery: An Overview Dragos Cristian Manta, Edward J Hu, Yoshua Bengio
ICML 2023 GFlowOut: Dropout with Generative Flow Networks 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
ICLR 2023 Generative Augmented Flow Networks Ling Pan, Dinghuai Zhang, Aaron Courville, Longbo Huang, Yoshua Bengio
ICML 2023 Hyena Hierarchy: Towards Larger Convolutional Language Models Michael Poli, Stefano Massaroli, Eric Nguyen, Daniel Y Fu, Tri Dao, Stephen Baccus, Yoshua Bengio, Stefano Ermon, Christopher Re
NeurIPS 2023 HyenaDNA: Long-Range Genomic Sequence Modeling at Single Nucleotide Resolution Eric Nguyen, Michael Poli, Marjan Faizi, Armin Thomas, Michael Wornow, Callum Birch-Sykes, Stefano Massaroli, Aman Patel, Clayton Rabideau, Yoshua Bengio, Stefano Ermon, Christopher Ré, Stephen Baccus
NeurIPS 2023 Improving *day-Ahead* Solar Irradiance Time Series Forecasting by Leveraging Spatio-Temporal Context Oussama Boussif, Ghait Boukachab, Dan Assouline, Stefano Massaroli, Tianle Yuan, Loubna Benabbou, Yoshua Bengio
ICMLW 2023 Improving and Generalizing Flow-Based Generative Models with Minibatch Optimal Transport Alexander Tong, Nikolay Malkin, Guillaume Huguet, Yanlei Zhang, Jarrid Rector-Brooks, Kilian Fatras, Guy Wolf, Yoshua Bengio
ICML 2023 Interventional Causal Representation Learning Kartik Ahuja, Divyat Mahajan, Yixin Wang, Yoshua Bengio
NeurIPS 2023 Joint Bayesian Inference of Graphical Structure and Parameters with a Single Generative Flow Network Tristan Deleu, Mizu Nishikawa-Toomey, Jithendaraa Subramanian, Nikolay Malkin, Laurent Charlin, Yoshua Bengio
ICMLW 2023 Joint Bayesian Inference of Graphical Structure and Parameters with a Single Generative Flow Network Tristan Deleu, Mizu Nishikawa-Toomey, Jithendaraa Subramanian, Nikolay Malkin, Laurent Charlin, Yoshua Bengio
ICLR 2023 Latent Bottlenecked Attentive Neural Processes Leo Feng, Hossein Hajimirsadeghi, Yoshua Bengio, Mohamed Osama Ahmed
ICLR 2023 Latent State Marginalization as a Low-Cost Approach for Improving Exploration Dinghuai Zhang, Aaron Courville, Yoshua Bengio, Qinqing Zheng, Amy Zhang, Ricky T. Q. Chen
NeurIPS 2023 Laughing Hyena Distillery: Extracting Compact Recurrences from Convolutions Stefano Massaroli, Michael Poli, Dan Fu, Hermann Kumbong, Rom Parnichkun, David Romero, Aman Timalsina, Quinn McIntyre, Beidi Chen, Atri Rudra, Ce Zhang, Christopher Ré, Stefano Ermon, Yoshua Bengio
ICML 2023 Learning GFlowNets from Partial Episodes for Improved Convergence and Stability Kanika Madan, Jarrid Rector-Brooks, Maksym Korablyov, Emmanuel Bengio, Moksh Jain, Andrei Cristian Nica, Tom Bosc, Yoshua Bengio, Nikolay Malkin
NeurIPSW 2023 Learning to Scale Logits for Temperature-Conditional GFlowNets Minsu Kim, Joohwan Ko, Dinghuai Zhang, Ling Pan, Taeyoung Yun, Woo Chang Kim, Jinkyoo Park, Yoshua Bengio
NeurIPS 2023 Let the Flows Tell: Solving Graph Combinatorial Problems with GFlowNets Dinghuai Zhang, Hanjun Dai, Nikolay Malkin, Aaron C. Courville, Yoshua Bengio, Ling Pan
UAI 2023 MixupE: Understanding and Improving Mixup from Directional Derivative Perspective Yingtian Zou, Vikas Verma, Sarthak Mittal, Wai Hoh Tang, Hieu Pham, Juho Kannala, Yoshua Bengio, Arno Solin, Kenji Kawaguchi
NeurIPSW 2023 Multi-Fidelity Active Learning with GFlowNets Alex Hernández-García, Nikita Saxena, Moksh Jain, Cheng-Hao Liu, Yoshua Bengio
ICML 2023 Multi-Objective GFlowNets Moksh Jain, Sharath Chandra Raparthy, Alex Hernández-Garcı́a, Jarrid Rector-Brooks, Yoshua Bengio, Santiago Miret, Emmanuel Bengio
TMLR 2023 Neural Causal Structure Discovery from Interventions Nan Rosemary Ke, Olexa Bilaniuk, Anirudh Goyal, Stefan Bauer, Hugo Larochelle, Bernhard Schölkopf, Michael Curtis Mozer, Christopher Pal, Yoshua Bengio
NeurIPSW 2023 Object-Centric Architectures Enable Efficient Causal Representation Learning Amin Mansouri, Jason Hartford, Yan Zhang, Yoshua Bengio
NeurIPSW 2023 On the Importance of Catalyst-Adsorbate 3D Interactions for Relaxed Energy Predictions Alvaro Carbonero, Alexandre AGM Duval, Victor Schmidt, Santiago Miret, Alex Hernández-García, Yoshua Bengio, David Rolnick
NeurIPSW 2023 Pre-Training and Fine-Tuning Generative Flow Networks Ling Pan, Moksh Jain, Kanika Madan, Yoshua Bengio
ICLR 2023 Predictive Inference with Feature Conformal Prediction Jiaye Teng, Chuan Wen, Dinghuai Zhang, Yoshua Bengio, Yang Gao, Yang Yuan
NeurIPS 2023 Reusable Slotwise Mechanisms Trang Nguyen, Amin Mansouri, Kanika Madan, Khuong Duy Nguyen, Kartik Ahuja, Dianbo Liu, Yoshua Bengio
ICLR 2023 Robust and Controllable Object-Centric Learning Through Energy-Based Models Ruixiang Zhang, Tong Che, Boris Ivanovic, Renhao Wang, Marco Pavone, Yoshua Bengio, Liam Paull
NeurIPS 2023 SatBird: A Dataset for Bird Species Distribution Modeling Using Remote Sensing and Citizen Science Data Mélisande Teng, Amna Elmustafa, Benjamin Akera, Yoshua Bengio, Hager Radi, Hugo Larochelle, David Rolnick
ICMLW 2023 Simulation-Free Schrödinger Bridges via Score and Flow Matching Alexander Tong, Nikolay Malkin, Kilian Fatras, Lazar Atanackovic, Yanlei Zhang, Guillaume Huguet, Guy Wolf, Yoshua Bengio
ICLR 2023 Stateful Active Facilitator: Coordination and Environmental Heterogeneity in Cooperative Multi-Agent Reinforcement Learning Dianbo Liu, Vedant Shah, Oussama Boussif, Cristian Meo, Anirudh Goyal, Tianmin Shu, Michael Curtis Mozer, Nicolas Heess, Yoshua Bengio
UAI 2023 Stochastic Generative Flow Networks Ling Pan, Dinghuai Zhang, Moksh Jain, Longbo Huang, Yoshua Bengio
ICML 2023 Synergies Between Disentanglement and Sparsity: Generalization and Identifiability in Multi-Task Learning Sebastien Lachapelle, Tristan Deleu, Divyat Mahajan, Ioannis Mitliagkas, Yoshua Bengio, Simon Lacoste-Julien, Quentin Bertrand
AAAI 2023 The Effect of Diversity in Meta-Learning Ramnath Kumar, Tristan Deleu, Yoshua Bengio
ICMLW 2023 Thompson Sampling for Improved Exploration in GFlowNets Jarrid Rector-Brooks, Kanika Madan, Moksh Jain, Maksym Korablyov, Cheng-Hao Liu, Sarath Chandar, Nikolay Malkin, Yoshua Bengio
NeurIPSW 2023 Towards Equilibrium Molecular Conformation Generation with GFlowNets Alexandra Volokhova, Michał Koziarski, Alex Hernández-García, Cheng-Hao Liu, Santiago Miret, Pablo Lemos, Luca Thiede, Zichao Yan, Alan Aspuru-Guzik, Yoshua Bengio
ICMLW 2023 What if We Enrich Day-Ahead Solar Irradiance Time Series Forecasting with Spatio-Temporal Context? Oussama Boussif, Ghait Boukachab, Dan Assouline, Stefano Massaroli, Tianle Yuan, Loubna Benabbou, Yoshua Bengio
NeurIPSW 2022 Bayesian Dynamic Causal Discovery Alexander Tong, Lazar Atanackovic, Jason Hartford, Yoshua Bengio
UAI 2022 Bayesian Structure Learning with Generative Flow Networks Tristan Deleu, António Góis, Chris Emezue, Mansi Rankawat, Simon Lacoste-Julien, Stefan Bauer, Yoshua Bengio
ICLRW 2022 Bayesian Structure Learning with Generative Flow Networks Tristan Deleu, António Góis, Chris Chinenye Emezue, Mansi Rankawat, Simon Lacoste-Julien, Stefan Bauer, Yoshua Bengio
ICML 2022 Biological Sequence Design with GFlowNets Moksh Jain, Emmanuel Bengio, Alex Hernandez-Garcia, Jarrid Rector-Brooks, Bonaventure F. P. Dossou, Chanakya Ajit Ekbote, Jie Fu, Tianyu Zhang, Michael Kilgour, Dinghuai Zhang, Lena Simine, Payel Das, Yoshua Bengio
ICML 2022 Building Robust Ensembles via Margin Boosting Dinghuai Zhang, Hongyang Zhang, Aaron Courville, Yoshua Bengio, Pradeep Ravikumar, Arun Sai Suggala
ICLR 2022 Chunked Autoregressive GAN for Conditional Waveform Synthesis Max Morrison, Rithesh Kumar, Kundan Kumar, Prem Seetharaman, Aaron Courville, Yoshua Bengio
ICLR 2022 ClimateGAN: Raising Climate Change Awareness by Generating Images of Floods Victor Schmidt, Alexandra Luccioni, Mélisande Teng, Tianyu Zhang, Alexia Reynaud, Sunand Raghupathi, Gautier Cosne, Adrien Juraver, Vahe Vardanyan, Alex Hernández-García, Yoshua Bengio
ICLR 2022 Compositional Attention: Disentangling Search and Retrieval Sarthak Mittal, Sharath Chandra Raparthy, Irina Rish, Yoshua Bengio, Guillaume Lajoie
ICLR 2022 Continuous-Time Meta-Learning with Forward Mode Differentiation Tristan Deleu, David Kanaa, Leo Feng, Giancarlo Kerg, Yoshua Bengio, Guillaume Lajoie, Pierre-Luc Bacon
NeurIPS 2022 Controlled Sparsity via Constrained Optimization or: How I Learned to Stop Tuning Penalties and Love Constraints Jose Gallego-Posada, Juan Ramirez, Akram Erraqabi, Yoshua Bengio, Simon Lacoste-Julien
ICLR 2022 Coordination Among Neural Modules Through a Shared Global Workspace Anirudh Goyal, Aniket Rajiv Didolkar, Alex Lamb, Kartikeya Badola, Nan Rosemary Ke, Nasim Rahaman, Jonathan Binas, Charles Blundell, Michael Curtis Mozer, Yoshua Bengio
NeurIPS 2022 Discrete Compositional Representations as an Abstraction for Goal Conditioned Reinforcement Learning Riashat Islam, Hongyu Zang, Anirudh Goyal, Alex M Lamb, Kenji Kawaguchi, Xin Li, Romain Laroche, Yoshua Bengio, Remi Tachet des Combes
NeurIPSW 2022 Efficient Queries Transformer Neural Processes Leo Feng, Hossein Hajimirsadeghi, Yoshua Bengio, Mohamed Osama Ahmed
NeurIPSW 2022 Equivariance with Learned Canonicalization Functions Sékou-Oumar Kaba, Arnab Kumar Mondal, Yan Zhang, Yoshua Bengio, Siamak Ravanbakhsh
ICLRW 2022 Evaluating Generalization in GFlowNets for Molecule Design Andrei Cristian Nica, Moksh Jain, Emmanuel Bengio, Cheng-Hao Liu, Maksym Korablyov, Michael M. Bronstein, Yoshua Bengio
NeurIPSW 2022 FL Games: A Federated Learning Framework for Distribution Shifts Sharut Gupta, Kartik Ahuja, Mohammad Havaei, Niladri Chatterjee, Yoshua Bengio
ICML 2022 Generative Flow Networks for Discrete Probabilistic Modeling Dinghuai Zhang, Nikolay Malkin, Zhen Liu, Alexandra Volokhova, Aaron Courville, Yoshua Bengio
ICLR 2022 Graph Neural Networks with Learnable Structural and Positional Representations Vijay Prakash Dwivedi, Anh Tuan Luu, Thomas Laurent, Yoshua Bengio, Xavier Bresson
ICLRW 2022 Inductive Biases for Relational Tasks Giancarlo Kerg, Sarthak Mittal, David Rolnick, Yoshua Bengio, Blake Aaron Richards, Guillaume Lajoie
NeurIPSW 2022 Interventional Causal Representation Learning Kartik Ahuja, Yixin Wang, Divyat Mahajan, Yoshua Bengio
NeurIPSW 2022 Interventional Causal Representation Learning Kartik Ahuja, Yixin Wang, Divyat Mahajan, Yoshua Bengio
NeurIPS 2022 Is a Modular Architecture Enough? Sarthak Mittal, Yoshua Bengio, Guillaume Lajoie
TMLR 2022 Lookback for Learning to Branch Prateek Gupta, Elias Boutros Khalil, Didier Chételat, Maxime Gasse, Andrea Lodi, Yoshua Bengio, M. Pawan Kumar
NeurIPS 2022 MAgNet: Mesh Agnostic Neural PDE Solver Oussama Boussif, Yoshua Bengio, Loubna Benabbou, Dan Assouline
ICMLW 2022 MAgNet: Mesh Agnostic Neural PDE Solver Oussama Boussif, Dan Assouline, Loubna Benabbou, Yoshua Bengio
NeurIPSW 2022 Multi-Objective GFlowNets Moksh Jain, Sharath Chandra Raparthy, Alex Hernández-García, Jarrid Rector-Brooks, Yoshua Bengio, Santiago Miret, Emmanuel Bengio
ICML 2022 Multi-Scale Feature Learning Dynamics: Insights for Double Descent Mohammad Pezeshki, Amartya Mitra, Yoshua Bengio, Guillaume Lajoie
NeurIPS 2022 Neural Attentive Circuits Martin Weiss, Nasim Rahaman, Francesco Locatello, Chris Pal, Yoshua Bengio, Bernhard Schölkopf, Erran Li Li, Nicolas Ballas
NeurIPSW 2022 Object-Centric Causal Representation Learning Amin Mansouri, Jason Hartford, Kartik Ahuja, Yoshua Bengio
ICLRW 2022 Object-Centric Compositional Imagination for Visual Abstract Reasoning Rim Assouel, Pau Rodriguez, Perouz Taslakian, David Vazquez, Yoshua Bengio
ICMLW 2022 On the Generalization and Adaption Performance of Causal Models Nino Scherrer, Anirudh Goyal, Stefan Bauer, Yoshua Bengio, Nan Rosemary Ke
NeurIPSW 2022 PhAST: Physics-Aware, Scalable, and Task-Specific GNNs for Accelerated Catalyst Design Alexandre AGM Duval, Victor Schmidt, Santiago Miret, Yoshua Bengio, Alex Hernández-García, David Rolnick
ICLR 2022 Properties from Mechanisms: An Equivariance Perspective on Identifiable Representation Learning Kartik Ahuja, Jason Hartford, Yoshua Bengio
NeurIPSW 2022 Rethinking Learning Dynamics in RL Using Adversarial Networks Ramnath Kumar, Tristan Deleu, Yoshua Bengio
UAI 2022 Temporal Abstractions-Augmented Temporally Contrastive Learning: An Alternative to the Laplacian in RL Akram Erraqabi, Marlos C. Machado, Mingde Zhao, Sainbayar Sukhbaatar, Alessandro Lazaric, Denoyer Ludovic, Yoshua Bengio
NeurIPS 2022 Temporal Latent Bottleneck: Synthesis of Fast and Slow Processing Mechanisms in Sequence Learning Aniket Didolkar, Kshitij Gupta, Anirudh Goyal, Nitesh Bharadwaj Gundavarapu, Alex M Lamb, Nan Rosemary Ke, Yoshua Bengio
ICML 2022 Towards Scaling Difference Target Propagation by Learning Backprop Targets Maxence M Ernoult, Fabrice Normandin, Abhinav Moudgil, Sean Spinney, Eugene Belilovsky, Irina Rish, Blake Richards, Yoshua Bengio
NeurIPS 2022 Trajectory Balance: Improved Credit Assignment in GFlowNets Nikolay Malkin, Moksh Jain, Emmanuel Bengio, Chen Sun, Yoshua Bengio
ICLR 2022 Unifying Likelihood-Free Inference with Black-Box Optimization and Beyond Dinghuai Zhang, Jie Fu, Yoshua Bengio, Aaron Courville
CLeaR 2022 VIM: Variational Independent Modules for Video Prediction Rim Assouel, Lluis Castrejon, Aaron Courville, Nicolas Ballas, Yoshua Bengio
NeurIPS 2022 Weakly Supervised Representation Learning with Sparse Perturbations Kartik Ahuja, Jason S Hartford, Yoshua Bengio
AISTATS 2021 An Analysis of the Adaptation Speed of Causal Models Rémi Le Priol, Reza Babanezhad, Yoshua Bengio, Simon Lacoste-Julien
AISTATS 2021 Neural Function Modules with Sparse Arguments: A Dynamic Approach to Integrating Information Across Layers Alex Lamb, Anirudh Goyal, Agnieszka Słowik, Michael Mozer, Philippe Beaudoin, Yoshua Bengio
NeurIPS 2021 A Consciousness-Inspired Planning Agent for Model-Based Reinforcement Learning Mingde Zhao, Zhen Liu, Sitao Luan, Shuyuan Zhang, Doina Precup, Yoshua Bengio
NeurIPSW 2021 A Consciousness-Inspired Planning Agent for Model-Based Reinforcement Learning Harry Zhao, Zhen Liu, Sitao Luan, Shuyuan Zhang, Doina Precup, Yoshua Bengio
ICML 2021 An End-to-End Framework for Molecular Conformation Generation via Bilevel Programming Minkai Xu, Wujie Wang, Shitong Luo, Chence Shi, Yoshua Bengio, Rafael Gomez-Bombarelli, Jian Tang
ICLR 2021 CausalWorld: A Robotic Manipulation Benchmark for Causal Structure and Transfer Learning Ossama Ahmed, Frederik Träuble, Anirudh Goyal, Alexander Neitz, Manuel Wuthrich, Yoshua Bengio, Bernhard Schölkopf, Stefan Bauer
AAAI 2021 Deep Verifier Networks: Verification of Deep Discriminative Models with Deep Generative Models Tong Che, Xiaofeng Liu, Site Li, Yubin Ge, Ruixiang Zhang, Caiming Xiong, Yoshua Bengio
NeurIPS 2021 Discrete-Valued Neural Communication Dianbo Liu, Alex M Lamb, Kenji Kawaguchi, Anirudh Goyal ALIAS PARTH Goyal, Chen Sun, Michael Mozer, Yoshua Bengio
NeurIPS 2021 Dynamic Inference with Neural Interpreters Nasim Rahaman, Muhammad Waleed Gondal, Shruti Joshi, Peter V. Gehler, Yoshua Bengio, Francesco Locatello, Bernhard Schölkopf
NeurIPSW 2021 Effect of Diversity in Meta-Learning Ramnath Kumar, Tristan Deleu, Yoshua Bengio
ICMLW 2021 Exploration-Driven Representation Learning in Reinforcement Learning Akram Erraqabi, Harry Zhao, Marlos C. Machado, Yoshua Bengio, Sainbayar Sukhbaatar, Ludovic Denoyer, Alessandro Lazaric
ICLR 2021 Factorizing Declarative and Procedural Knowledge in Structured, Dynamical Environments Anirudh Goyal, Alex Lamb, Phanideep Gampa, Philippe Beaudoin, Charles Blundell, Sergey Levine, Yoshua Bengio, Michael Curtis Mozer
ICLR 2021 Fast and Slow Learning of Recurrent Independent Mechanisms Kanika Madan, Nan Rosemary Ke, Anirudh Goyal, Bernhard Schölkopf, Yoshua Bengio
ICCV 2021 FloW: A Dataset and Benchmark for Floating Waste Detection in Inland Waters Yuwei Cheng, Jiannan Zhu, Mengxin Jiang, Jie Fu, Changsong Pang, Peidong Wang, Kris Sankaran, Olawale Onabola, Yimin Liu, Dianbo Liu, Yoshua Bengio
NeurIPS 2021 Flow Network Based Generative Models for Non-Iterative Diverse Candidate Generation Emmanuel Bengio, Moksh Jain, Maksym Korablyov, Doina Precup, Yoshua Bengio
NeurIPS 2021 Gradient Starvation: A Learning Proclivity in Neural Networks Mohammad Pezeshki, Oumar Kaba, Yoshua Bengio, Aaron C. Courville, Doina Precup, Guillaume Lajoie
AAAI 2021 GraphMix: Improved Training of GNNs for Semi-Supervised Learning Vikas Verma, Meng Qu, Kenji Kawaguchi, Alex Lamb, Yoshua Bengio, Juho Kannala, Jian Tang
NeurIPS 2021 Invariance Principle Meets Information Bottleneck for Out-of-Distribution Generalization Kartik Ahuja, Ethan Caballero, Dinghuai Zhang, Jean-Christophe Gagnon-Audet, Yoshua Bengio, Ioannis Mitliagkas, Irina Rish
ICLR 2021 Learning Neural Generative Dynamics for Molecular Conformation Generation Minkai Xu, Shitong Luo, Yoshua Bengio, Jian Peng, Jian Tang
NeurIPSW 2021 Long-Term Credit Assignment via Model-Based Temporal Shortcuts Michel Ma, Pierluca D'Oro, Yoshua Bengio, Pierre-Luc Bacon
AAAI 2021 Meta-Learning Framework with Applications to Zero-Shot Time-Series Forecasting Boris N. Oreshkin, Dmitri Carpov, Nicolas Chapados, Yoshua Bengio
NeurIPS 2021 Neural Production Systems Anirudh Goyal ALIAS PARTH Goyal, Aniket Didolkar, Nan Rosemary Ke, Charles Blundell, Philippe Beaudoin, Nicolas Heess, Michael Mozer, Yoshua Bengio
AAAI 2021 Object-Centric Image Generation from Layouts Tristan Sylvain, Pengchuan Zhang, Yoshua Bengio, R. Devon Hjelm, Shikhar Sharma
AAAI 2021 Parameterizing Branch-and-Bound Search Trees to Learn Branching Policies Giulia Zarpellon, Jason Jo, Andrea Lodi, Yoshua Bengio
ICLR 2021 Predicting Infectiousness for Proactive Contact Tracing Yoshua Bengio, Prateek Gupta, Tegan Maharaj, Nasim Rahaman, Martin Weiss, Tristan Deleu, Eilif Benjamin Muller, Meng Qu, Victor Schmidt, Pierre-Luc St-Charles, Hannah Alsdurf, Olexa Bilaniuk, David Buckeridge, Gaetan Caron, Pierre Luc Carrier, Joumana Ghosn, Satya Ortiz Gagne, Christopher Pal, Irina Rish, Bernhard Schölkopf, Abhinav Sharma, Jian Tang, Andrew Williams
ICLR 2021 RNNLogic: Learning Logic Rules for Reasoning on Knowledge Graphs Meng Qu, Junkun Chen, Louis-Pascal Xhonneux, Yoshua Bengio, Jian Tang
ICLR 2021 Recurrent Independent Mechanisms Anirudh Goyal, Alex Lamb, Jordan Hoffmann, Shagun Sodhani, Sergey Levine, Yoshua Bengio, Bernhard Schölkopf
ICLR 2021 Saliency Is a Possible Red Herring When Diagnosing Poor Generalization Joseph D Viviano, Becks Simpson, Francis Dutil, Yoshua Bengio, Joseph Paul Cohen
ICLR 2021 Spatially Structured Recurrent Modules Nasim Rahaman, Anirudh Goyal, Muhammad Waleed Gondal, Manuel Wuthrich, Stefan Bauer, Yash Sharma, Yoshua Bengio, Bernhard Schölkopf
ICLR 2021 Systematic Generalisation with Group Invariant Predictions Faruk Ahmed, Yoshua Bengio, Harm van Seijen, Aaron Courville
NeurIPS 2021 The Causal-Neural Connection: Expressiveness, Learnability, and Inference Kevin Xia, Kai-Zhan Lee, Yoshua Bengio, Elias Bareinboim
AAAI 2021 Visual Concept Reasoning Networks Taesup Kim, Sungwoong Kim, Yoshua Bengio
ICLR 2020 A Meta-Transfer Objective for Learning to Disentangle Causal Mechanisms Yoshua Bengio, Tristan Deleu, Nasim Rahaman, Rosemary Ke, Sébastien Lachapelle, Olexa Bilaniuk, Anirudh Goyal, Christopher Pal
AAAI 2020 Combating False Negatives in Adversarial Imitation Learning (Student Abstract) Konrad Zolna, Chitwan Saharia, Léonard Boussioux, David Yu-Tung Hui, Maxime Chevalier-Boisvert, Dzmitry Bahdanau, Yoshua Bengio
ECCV 2020 DiVA: Diverse Visual Feature Aggregation for Deep Metric Learning Timo Milbich, Karsten Roth, Homanga Bharadhwaj, Samarth Sinha, Yoshua Bengio, Björn Ommer, Joseph Paul Cohen
ICLR 2020 HighRes-Net: Multi-Frame Super-Resolution by Recursive Fusion Michel Deudon, Alfredo Kalaitzis, Md Rifat Arefin, Israel Goytom, Zhichao Lin, Kris Sankaran, Vincent Michalski, Samira E Kahou, Julien Cornebise, Yoshua Bengio
NeurIPS 2020 Hybrid Models for Learning to Branch Prateek Gupta, Maxime Gasse, Elias Khalil, Pawan Mudigonda, Andrea Lodi, Yoshua Bengio
ICLR 2020 Hyperbolic Discounting and Learning over Multiple Horizons William Fedus, Carles Gelada, Yoshua Bengio, Marc G. Bellemare, Hugo Larochelle
ICLR 2020 Learning the Arrow of Time for Problems in Reinforcement Learning Nasim Rahaman, Steffen Wolf, Anirudh Goyal, Roman Remme, Yoshua Bengio
ICML 2020 Learning to Combine Top-Down and Bottom-up Signals in Recurrent Neural Networks with Attention over Modules Sarthak Mittal, Alex Lamb, Anirudh Goyal, Vikram Voleti, Murray Shanahan, Guillaume Lajoie, Michael Mozer, Yoshua Bengio
ICML 2020 Learning to Navigate the Synthetically Accessible Chemical Space Using Reinforcement Learning Sai Krishna Gottipati, Boris Sattarov, Sufeng Niu, Yashaswi Pathak, Haoran Wei, Shengchao Liu, Shengchao Liu, Simon Blackburn, Karam Thomas, Connor Coley, Jian Tang, Sarath Chandar, Yoshua Bengio
CVPRW 2020 Multi-Image Super-Resolution for Remote Sensing Using Deep Recurrent Networks Md Rifat Arefin, Vincent Michalski, Pierre-Luc St-Charles, Alfredo Kalaitzis, Sookyung Kim, Samira Ebrahimi Kahou, Yoshua Bengio
ICLR 2020 N-BEATS: Neural Basis Expansion Analysis for Interpretable Time Series Forecasting Boris N. Oreshkin, Dmitri Carpov, Nicolas Chapados, Yoshua Bengio
AISTATS 2020 On the Interplay Between Noise and Curvature and Its Effect on Optimization and Generalization Valentin Thomas, Fabian Pedregosa, Bart Merriënboer, Pierre-Antoine Manzagol, Yoshua Bengio, Nicolas Le Roux
ICML 2020 Perceptual Generative Autoencoders Zijun Zhang, Ruixiang Zhang, Zongpeng Li, Yoshua Bengio, Liam Paull
ICLR 2020 Reinforcement Learning with Competitive Ensembles of Information-Constrained Primitives Anirudh Goyal, Shagun Sodhani, Jonathan Binas, Xue Bin Peng, Sergey Levine, Yoshua Bengio
ICML 2020 Revisiting Fundamentals of Experience Replay William Fedus, Prajit Ramachandran, Rishabh Agarwal, Yoshua Bengio, Hugo Larochelle, Mark Rowland, Will Dabney
ICML 2020 Small-GAN: Speeding up GAN Training Using Core-Sets Samarth Sinha, Han Zhang, Anirudh Goyal, Yoshua Bengio, Hugo Larochelle, Augustus Odena
JAIR 2020 The Bottleneck Simulator: A Model-Based Deep Reinforcement Learning Approach Iulian Vlad Serban, Chinnadhurai Sankar, Michael Pieper, Joelle Pineau, Yoshua Bengio
ICLR 2020 The Variational Bandwidth Bottleneck: Stochastic Evaluation on an Information Budget Anirudh Goyal, Yoshua Bengio, Matthew Botvinick, Sergey Levine
NeurIPS 2020 Untangling Tradeoffs Between Recurrence and Self-Attention in Artificial Neural Networks Giancarlo Kerg, Bhargav Kanuparthi, Anirudh Goyal ALIAS PARTH Goyal, Kyle Goyette, Yoshua Bengio, Guillaume Lajoie
NeurIPS 2020 Your GAN Is Secretly an Energy-Based Model and You Should Use Discriminator Driven Latent Sampling Tong Che, Ruixiang Zhang, Jascha Sohl-Dickstein, Hugo Larochelle, Liam Paull, Yuan Cao, Yoshua Bengio
ICLR 2019 Adversarial Domain Adaptation for Stable Brain-Machine Interfaces Ali Farshchian, Juan A. Gallego, Joseph P. Cohen, Yoshua Bengio, Lee E. Miller, Sara A. Solla
ICLR 2019 An Empirical Study of Example Forgetting During Deep Neural Network Learning Mariya Toneva, Alessandro Sordoni, Remi Tachet des Combes, Adam Trischler, Yoshua Bengio, Geoffrey J. Gordon
ICLR 2019 BabyAI: A Platform to Study the Sample Efficiency of Grounded Language Learning Maxime Chevalier-Boisvert, Dzmitry Bahdanau, Salem Lahlou, Lucas Willems, Chitwan Saharia, Thien Huu Nguyen, Yoshua Bengio
AAAI 2019 Combined Reinforcement Learning via Abstract Representations Vincent François-Lavet, Yoshua Bengio, Doina Precup, Joelle Pineau
ICLR 2019 Deep Graph Infomax Petar Veličković, William Fedus, William L. Hamilton, Pietro Liò, Yoshua Bengio, R Devon Hjelm
ICML 2019 GMNN: Graph Markov Neural Networks Meng Qu, Yoshua Bengio, Jian Tang
NeurIPS 2019 Gradient Based Sample Selection for Online Continual Learning Rahaf Aljundi, Min Lin, Baptiste Goujaud, Yoshua Bengio
ICLR 2019 H-Detach: Modifying the LSTM Gradient Towards Better Optimization Bhargav Kanuparthi, Devansh Arpit, Giancarlo Kerg, Nan Rosemary Ke, Ioannis Mitliagkas, Yoshua Bengio
NeurIPS 2019 How to Initialize Your Network? Robust Initialization for WeightNorm & ResNets Devansh Arpit, Víctor Campos, Yoshua Bengio
ICLR 2019 InfoBot: Transfer and Exploration via the Information Bottleneck Anirudh Goyal, Riashat Islam, Dj Strouse, Zafarali Ahmed, Hugo Larochelle, Matthew Botvinick, Yoshua Bengio, Sergey Levine
IJCAI 2019 Interpolation Consistency Training for Semi-Supervised Learning Vikas Verma, Alex Lamb, Juho Kannala, Yoshua Bengio, David Lopez-Paz
ICLR 2019 Learning Deep Representations by Mutual Information Estimation and Maximization R Devon Hjelm, Alex Fedorov, Samuel Lavoie-Marchildon, Karan Grewal, Phil Bachman, Adam Trischler, Yoshua Bengio
ICML 2019 Manifold Mixup: Better Representations by Interpolating Hidden States Vikas Verma, Alex Lamb, Christopher Beckham, Amir Najafi, Ioannis Mitliagkas, David Lopez-Paz, Yoshua Bengio
NeurIPS 2019 MelGAN: Generative Adversarial Networks for Conditional Waveform Synthesis Kundan Kumar, Rithesh Kumar, Thibault de Boissiere, Lucas Gestin, Wei Zhen Teoh, Jose Sotelo, Alexandre de Brébisson, Yoshua Bengio, Aaron C. Courville
ICLR 2019 Modeling the Long Term Future in Model-Based Reinforcement Learning Nan Rosemary Ke, Amanpreet Singh, Ahmed Touati, Anirudh Goyal, Yoshua Bengio, Devi Parikh, Dhruv Batra
NeurIPS 2019 Non-Normal Recurrent Neural Network (nnRNN): Learning Long Time Dependencies While Improving Expressivity with Transient Dynamics Giancarlo Kerg, Kyle Goyette, Maximilian Puelma Touzel, Gauthier Gidel, Eugene Vorontsov, Yoshua Bengio, Guillaume Lajoie
NeurIPS 2019 On Adversarial Mixup Resynthesis Christopher Beckham, Sina Honari, Vikas Verma, Alex M Lamb, Farnoosh Ghadiri, R Devon Hjelm, Yoshua Bengio, Chris Pal
ICLR 2019 On the Relation Between the Sharpest Directions of DNN Loss and the SGD Step Length Stanisław Jastrzębski, Zachary Kenton, Nicolas Ballas, Asja Fischer, Yoshua Bengio, Amos Storkey
ICML 2019 On the Spectral Bias of Neural Networks Nasim Rahaman, Aristide Baratin, Devansh Arpit, Felix Draxler, Min Lin, Fred Hamprecht, Yoshua Bengio, Aaron Courville
ICLRW 2019 Perceptual Generative Autoencoders Zijun Zhang, Ruixiang Zhang, Zongpeng Li, Yoshua Bengio, Liam Paull
ICLR 2019 Probabilistic Planning with Sequential Monte Carlo Methods Alexandre Piche, Valentin Thomas, Cyril Ibrahim, Yoshua Bengio, Chris Pal
ICLR 2019 Quaternion Recurrent Neural Networks Titouan Parcollet, Mirco Ravanelli, Mohamed Morchid, Georges Linarès, Chiheb Trabelsi, Renato De Mori, Yoshua Bengio
ICLR 2019 Recall Traces: Backtracking Models for Efficient Reinforcement Learning Anirudh Goyal, Philemon Brakel, William Fedus, Soumye Singhal, Timothy Lillicrap, Sergey Levine, Hugo Larochelle, Yoshua Bengio
ICML 2019 State-Reification Networks: Improving Generalization by Modeling the Distribution of Hidden Representations Alex Lamb, Jonathan Binas, Anirudh Goyal, Sandeep Subramanian, Ioannis Mitliagkas, Yoshua Bengio, Michael Mozer
AAAI 2019 Towards Non-Saturating Recurrent Units for Modelling Long-Term Dependencies Sarath Chandar, Chinnadhurai Sankar, Eugene Vorontsov, Samira Ebrahimi Kahou, Yoshua Bengio
NeurIPS 2019 Unsupervised State Representation Learning in Atari Ankesh Anand, Evan Racah, Sherjil Ozair, Yoshua Bengio, Marc-Alexandre Côté, R Devon Hjelm
NeurIPS 2019 Updates of Equilibrium Prop Match Gradients of Backprop Through Time in an RNN with Static Input Maxence Ernoult, Julie Grollier, Damien Querlioz, Yoshua Bengio, Benjamin Scellier
NeurIPS 2019 Variational Temporal Abstraction Taesup Kim, Sungjin Ahn, Yoshua Bengio
NeurIPS 2019 Wasserstein Dependency Measure for Representation Learning Sherjil Ozair, Corey Lynch, Yoshua Bengio, Aaron van den Oord, Sergey Levine, Pierre Sermanet
NeurIPS 2018 Bayesian Model-Agnostic Meta-Learning Jaesik Yoon, Taesup Kim, Ousmane Dia, Sungwoong Kim, Yoshua Bengio, Sungjin Ahn
ICLR 2018 Boundary Seeking GANs R Devon Hjelm, Athul Paul Jacob, Adam Trischler, Gerry Che, Kyunghyun Cho, Yoshua Bengio
ICLR 2018 Deep Complex Networks Chiheb Trabelsi, Olexa Bilaniuk, Ying Zhang, Dmitriy Serdyuk, Sandeep Subramanian, Joao Felipe Santos, Soroush Mehri, Negar Rostamzadeh, Yoshua Bengio, Christopher J Pal
NeurIPS 2018 Dendritic Cortical Microcircuits Approximate the Backpropagation Algorithm João Sacramento, Rui Ponte Costa, Yoshua Bengio, Walter Senn
Distill 2018 Feature-Wise Transformations Vincent Dumoulin, Ethan Perez, Nathan Schucher, Florian Strub, Harm de Vries, Aaron Courville, Yoshua Bengio
ICML 2018 Focused Hierarchical RNNs for Conditional Sequence Processing Nan Rosemary Ke, Konrad Żołna, Alessandro Sordoni, Zhouhan Lin, Adam Trischler, Yoshua Bengio, Joelle Pineau, Laurent Charlin, Christopher Pal
ICLR 2018 Fraternal Dropout Konrad Zolna, Devansh Arpit, Dendi Suhubdy, Yoshua Bengio
ICLR 2018 Graph Attention Networks Petar Veličković, Guillem Cucurull, Arantxa Casanova, Adriana Romero, Pietro Liò, Yoshua Bengio
NeurIPS 2018 Image-to-Image Translation for Cross-Domain Disentanglement Abel Gonzalez-Garcia, Joost van de Weijer, Yoshua Bengio
ICLR 2018 Learning General Purpose Distributed Sentence Representations via Large Scale Multi-Task Learning Sandeep Subramanian, Adam Trischler, Yoshua Bengio, Christopher J Pal
NeurIPS 2018 MetaGAN: An Adversarial Approach to Few-Shot Learning Ruixiang Zhang, Tong Che, Zoubin Ghahramani, Yoshua Bengio, Yangqiu Song
ICML 2018 Mutual Information Neural Estimation Mohamed Ishmael Belghazi, Aristide Baratin, Sai Rajeshwar, Sherjil Ozair, Yoshua Bengio, Aaron Courville, Devon Hjelm
CVPRW 2018 On the Iterative Refinement of Densely Connected Representation Levels for Semantic Segmentation Arantxa Casanova, Guillem Cucurull, Michal Drozdzal, Adriana Romero, Yoshua Bengio
ICLR 2018 Residual Connections Encourage Iterative Inference Stanisław Jastrzebski, Devansh Arpit, Nicolas Ballas, Vikas Verma, Tong Che, Yoshua Bengio
NeurIPS 2018 Sparse Attentive Backtracking: Temporal Credit Assignment Through Reminding Nan Rosemary Ke, Anirudh Goyal ALIAS PARTH Goyal, Olexa Bilaniuk, Jonathan Binas, Michael Mozer, Chris Pal, Yoshua Bengio
ICLR 2018 Twin Networks: Matching the Future for Sequence Generation Dmitriy Serdyuk, Nan Rosemary Ke, Alessandro Sordoni, Adam Trischler, Chris Pal, Yoshua Bengio
ICML 2017 A Closer Look at Memorization in Deep Networks Devansh Arpit, Stanisław Jastrzębski, Nicolas Ballas, David Krueger, Emmanuel Bengio, Maxinder S. Kanwal, Tegan Maharaj, Asja Fischer, Aaron Courville, Yoshua Bengio, Simon Lacoste-Julien
AAAI 2017 A Hierarchical Latent Variable Encoder-Decoder Model for Generating Dialogues Iulian Vlad Serban, Alessandro Sordoni, Ryan Lowe, Laurent Charlin, Joelle Pineau, Aaron C. Courville, Yoshua Bengio
ICLR 2017 A Structured Self-Attentive Sentence Embedding Zhouhan Lin, Minwei Feng, Cícero Nogueira dos Santos, Mo Yu, Bing Xiang, Bowen Zhou, Yoshua Bengio
ICLR 2017 An Actor-Critic Algorithm for Sequence Prediction Dzmitry Bahdanau, Philemon Brakel, Kelvin Xu, Anirudh Goyal, Ryan Lowe, Joelle Pineau, Aaron C. Courville, Yoshua Bengio
ICLR 2017 Char2Wav: End-to-End Speech Synthesis Jose Sotelo, Soroush Mehri, Kundan Kumar, João Felipe Santos, Kyle Kastner, Aaron C. Courville, Yoshua Bengio
ICCVW 2017 Count-Ception: Counting by Fully Convolutional Redundant Counting Joseph Paul Cohen, Geneviève Boucher, Craig A. Glastonbury, Henry Z. Lo, Yoshua Bengio
AAAI 2017 Denoising Criterion for Variational Auto-Encoding Framework Daniel Jiwoong Im, Sungjin Ahn, Roland Memisevic, Yoshua Bengio
ICLR 2017 Diet Networks: Thin Parameters for Fat Genomics Adriana Romero, Pierre Luc Carrier, Akram Erraqabi, Tristan Sylvain, Alex Auvolat, Etienne Dejoie, Marc-André Legault, Marie-Pierre Dubé, Julie G. Hussin, Yoshua Bengio
ICLR 2017 Generalizable Features from Unsupervised Learning Mehdi Mirza, Aaron C. Courville, Yoshua Bengio
NeurIPS 2017 GibbsNet: Iterative Adversarial Inference for Deep Graphical Models Alex M Lamb, Devon Hjelm, Yaroslav Ganin, Joseph Paul Cohen, Aaron C. Courville, Yoshua Bengio
ICLR 2017 Hierarchical Multiscale Recurrent Neural Networks Junyoung Chung, Sungjin Ahn, Yoshua Bengio
ICLR 2017 Improving Generative Adversarial Networks with Denoising Feature Matching David Warde-Farley, Yoshua Bengio
ICLR 2017 Mode Regularized Generative Adversarial Networks Tong Che, Yanran Li, Athul Paul Jacob, Yoshua Bengio, Wenjie Li
ICLR 2017 Mollifying Networks Çaglar Gülçehre, Marcin Moczulski, Francesco Visin, Yoshua Bengio
AAAI 2017 Multiresolution Recurrent Neural Networks: An Application to Dialogue Response Generation Iulian Vlad Serban, Tim Klinger, Gerald Tesauro, Kartik Talamadupula, Bowen Zhou, Yoshua Bengio, Aaron C. Courville
NeurIPS 2017 Plan, Attend, Generate: Planning for Sequence-to-Sequence Models Caglar Gulcehre, Francis Dutil, Adam Trischler, Yoshua Bengio
CVPR 2017 Plug & Play Generative Networks: Conditional Iterative Generation of Images in Latent Space Anh Nguyen, Jeff Clune, Yoshua Bengio, Alexey Dosovitskiy, Jason Yosinski
ICLR 2017 SampleRNN: An Unconditional End-to-End Neural Audio Generation Model Soroush Mehri, Kundan Kumar, Ishaan Gulrajani, Rithesh Kumar, Shubham Jain, Jose Sotelo, Aaron C. Courville, Yoshua Bengio
ICML 2017 Sharp Minima Can Generalize for Deep Nets Laurent Dinh, Razvan Pascanu, Samy Bengio, Yoshua Bengio
CVPRW 2017 The One Hundred Layers Tiramisu: Fully Convolutional DenseNets for Semantic Segmentation Simon Jégou, Michal Drozdzal, David Vázquez, Adriana Romero, Yoshua Bengio
ICLR 2017 Towards an Automatic Turing Test: Learning to Evaluate Dialogue Responses Ryan Lowe, Michael Noseworthy, Iulian Vlad Serban, Nicolas Angelard-Gontier, Yoshua Bengio, Joelle Pineau
ICLR 2017 Understanding Intermediate Layers Using Linear Classifier Probes Guillaume Alain, Yoshua Bengio
NeurIPS 2017 Variational Walkback: Learning a Transition Operator as a Stochastic Recurrent Net Anirudh Goyal ALIAS PARTH Goyal, Nan Rosemary Ke, Surya Ganguli, Yoshua Bengio
NeurIPS 2017 Z-Forcing: Training Stochastic Recurrent Networks Anirudh Goyal ALIAS PARTH Goyal, Alessandro Sordoni, Marc-Alexandre Côté, Nan Rosemary Ke, Yoshua Bengio
ICLR 2017 Zoneout: Regularizing RNNs by Randomly Preserving Hidden Activations David Krueger, Tegan Maharaj, János Kramár, Mohammad Pezeshki, Nicolas Ballas, Nan Rosemary Ke, Anirudh Goyal, Yoshua Bengio, Aaron C. Courville, Christopher J. Pal
ICLR 2016 4th International Conference on Learning Representations, ICLR 2016, San Juan, Puerto Rico, May 2-4, 2016, Conference Track Proceedings Yoshua Bengio, Yann LeCun
NeurIPS 2016 Architectural Complexity Measures of Recurrent Neural Networks Saizheng Zhang, Yuhuai Wu, Tong Che, Zhouhan Lin, Roland Memisevic, Ruslan Salakhutdinov, Yoshua Bengio
ICML 2016 Bidirectional Helmholtz Machines Jorg Bornschein, Samira Shabanian, Asja Fischer, Yoshua Bengio
NeurIPS 2016 Binarized Neural Networks Itay Hubara, Matthieu Courbariaux, Daniel Soudry, Ran El-Yaniv, Yoshua Bengio
AAAI 2016 Building End-to-End Dialogue Systems Using Generative Hierarchical Neural Network Models Iulian Vlad Serban, Alessandro Sordoni, Yoshua Bengio, Aaron C. Courville, Joelle Pineau
ICML 2016 Deconstructing the Ladder Network Architecture Mohammad Pezeshki, Linxi Fan, Philemon Brakel, Aaron Courville, Yoshua Bengio
JMLR 2016 Knowledge Matters: Importance of Prior Information for Optimization Çağlar Gülçehre, Yoshua Bengio
ICLR 2016 Neural Networks with Few Multiplications Zhouhan Lin, Matthieu Courbariaux, Roland Memisevic, Yoshua Bengio
ICML 2016 Noisy Activation Functions Caglar Gulcehre, Marcin Moczulski, Misha Denil, Yoshua Bengio
NeurIPS 2016 On Multiplicative Integration with Recurrent Neural Networks Yuhuai Wu, Saizheng Zhang, Ying Zhang, Yoshua Bengio, Ruslan Salakhutdinov
NeurIPS 2016 Professor Forcing: A New Algorithm for Training Recurrent Networks Alex M Lamb, Anirudh Goyal ALIAS PARTH Goyal, Ying Zhang, Saizheng Zhang, Aaron C. Courville, Yoshua Bengio
CVPRW 2016 ReSeg: A Recurrent Neural Network-Based Model for Semantic Segmentation Francesco Visin, Adriana Romero, Kyunghyun Cho, Matteo Matteucci, Marco Ciccone, Kyle Kastner, Yoshua Bengio, Aaron C. Courville
ICML 2016 Unitary Evolution Recurrent Neural Networks Martin Arjovsky, Amar Shah, Yoshua Bengio
ICLR 2015 3rd International Conference on Learning Representations, ICLR 2015, San Diego, CA, USA, May 7-9, 2015, Conference Track Proceedings Yoshua Bengio, Yann LeCun
ICLR 2015 3rd International Conference on Learning Representations, ICLR 2015, San Diego, CA, USA, May 7-9, 2015, Workshop Track Proceedings Yoshua Bengio, Yann LeCun
NeurIPS 2015 A Recurrent Latent Variable Model for Sequential Data Junyoung Chung, Kyle Kastner, Laurent Dinh, Kratarth Goel, Aaron C. Courville, Yoshua Bengio
NeurIPS 2015 Attention-Based Models for Speech Recognition Jan K Chorowski, Dzmitry Bahdanau, Dmitriy Serdyuk, Kyunghyun Cho, Yoshua Bengio
ICML 2015 BilBOWA: Fast Bilingual Distributed Representations Without Word Alignments Stephan Gouws, Yoshua Bengio, Greg Corrado
NeurIPS 2015 BinaryConnect: Training Deep Neural Networks with Binary Weights During Propagations Matthieu Courbariaux, Yoshua Bengio, Jean-Pierre David
ECML-PKDD 2015 Difference Target Propagation Dong-Hyun Lee, Saizheng Zhang, Asja Fischer, Yoshua Bengio
ICLR 2015 Embedding Word Similarity with Neural Machine Translation Felix Hill, Kyunghyun Cho, Sébastien Jean, Coline Devin, Yoshua Bengio
ICLR 2015 Ensemble of Generative and Discriminative Techniques for Sentiment Analysis of Movie Reviews Grégoire Mesnil, Tomás Mikolov, Marc'Aurelio Ranzato, Yoshua Bengio
NeurIPS 2015 Equilibrated Adaptive Learning Rates for Non-Convex Optimization Yann Dauphin, Harm de Vries, Yoshua Bengio
ICLR 2015 FitNets: Hints for Thin Deep Nets Adriana Romero, Nicolas Ballas, Samira Ebrahimi Kahou, Antoine Chassang, Carlo Gatta, Yoshua Bengio
ICML 2015 Gated Feedback Recurrent Neural Networks Junyoung Chung, Caglar Gulcehre, Kyunghyun Cho, Yoshua Bengio
ICLR 2015 Low Precision Arithmetic for Deep Learning Matthieu Courbariaux, Yoshua Bengio, Jean-Pierre David
ICLR 2015 NICE: Non-Linear Independent Components Estimation Laurent Dinh, David Krueger, Yoshua Bengio
ICLR 2015 Neural Machine Translation by Jointly Learning to Align and Translate Dzmitry Bahdanau, Kyunghyun Cho, Yoshua Bengio
ICLR 2015 Reweighted Wake-Sleep Jörg Bornschein, Yoshua Bengio
ICML 2015 Show, Attend and Tell: Neural Image Caption Generation with Visual Attention Kelvin Xu, Jimmy Ba, Ryan Kiros, Kyunghyun Cho, Aaron Courville, Ruslan Salakhudinov, Rich Zemel, Yoshua Bengio
ICLR 2015 Target Propagation Dong-Hyun Lee, Saizheng Zhang, Antoine Biard, Yoshua Bengio
ICLR 2014 2nd International Conference on Learning Representations, ICLR 2014, Banff, AB, Canada, April 14-16, 2014, Conference Track Proceedings Yoshua Bengio, Yann LeCun
ICLR 2014 2nd International Conference on Learning Representations, ICLR 2014, Banff, AB, Canada, April 14-16, 2014, Workshop Track Proceedings Yoshua Bengio, Yann LeCun
MLJ 2014 A Semantic Matching Energy Function for Learning with Multi-Relational Data - Application to Word-Sense Disambiguation Antoine Bordes, Xavier Glorot, Jason Weston, Yoshua Bengio
ICLR 2014 An Empirical Analysis of Dropout in Piecewise Linear Networks David Warde-Farley, Ian J. Goodfellow, Aaron C. Courville, Yoshua Bengio
ICLR 2014 An Empirical Investigation of Catastrophic Forgeting in Gradient-Based Neural Networks Ian J. Goodfellow, Mehdi Mirza, Xia Da, Aaron C. Courville, Yoshua Bengio
ICLR 2014 Bounding the Test Log-Likelihood of Generative Models Yoshua Bengio, Li Yao
ICML 2014 Deep Generative Stochastic Networks Trainable by Backprop Yoshua Bengio, Eric Laufer, Guillaume Alain, Jason Yosinski
NeurIPS 2014 Generative Adversarial Nets Ian Goodfellow, Jean Pouget-Abadie, Mehdi Mirza, Bing Xu, David Warde-Farley, Sherjil Ozair, Aaron Courville, Yoshua Bengio
NeurIPS 2014 How Transferable Are Features in Deep Neural Networks? Jason Yosinski, Jeff Clune, Yoshua Bengio, Hod Lipson
ICLR 2014 How to Construct Deep Recurrent Neural Networks Razvan Pascanu, Çaglar Gülçehre, Kyunghyun Cho, Yoshua Bengio
NeurIPS 2014 Identifying and Attacking the Saddle Point Problem in High-Dimensional Non-Convex Optimization Yann N. Dauphin, Razvan Pascanu, Caglar Gulcehre, Kyunghyun Cho, Surya Ganguli, Yoshua Bengio
NeurIPS 2014 Iterative Neural Autoregressive Distribution Estimator NADE-K Tapani Raiko, Yao Li, Kyunghyun Cho, Yoshua Bengio
ECML-PKDD 2014 Learned-Norm Pooling for Deep Feedforward and Recurrent Neural Networks Çaglar Gülçehre, KyungHyun Cho, Razvan Pascanu, Yoshua Bengio
AAAI 2014 Learning Concept Embeddings for Query Expansion by Quantum Entropy Minimization Alessandro Sordoni, Yoshua Bengio, Jian-Yun Nie
MLJ 2014 Learning Semantic Representations of Objects and Their Parts Grégoire Mesnil, Antoine Bordes, Jason Weston, Gal Chechik, Yoshua Bengio
ICML 2014 Marginalized Denoising Auto-Encoders for Nonlinear Representations Minmin Chen, Kilian Weinberger, Fei Sha, Yoshua Bengio
ICLR 2014 Multimodal Transitions for Generative Stochastic Networks Sherjil Ozair, Li Yao, Yoshua Bengio
AAAI 2014 On the Challenges of Physical Implementations of RBMs Vincent Dumoulin, Ian J. Goodfellow, Aaron C. Courville, Yoshua Bengio
ECML-PKDD 2014 On the Equivalence Between Deep NADE and Generative Stochastic Networks Li Yao, Sherjil Ozair, KyungHyun Cho, Yoshua Bengio
ICLR 2014 On the Number of Inference Regions of Deep Feed Forward Networks with Piece-Wise Linear Activations Razvan Pascanu, Guido Montúfar, Yoshua Bengio
NeurIPS 2014 On the Number of Linear Regions of Deep Neural Networks Guido F. Montufar, Razvan Pascanu, Kyunghyun Cho, Yoshua Bengio
ICLR 2014 Revisiting Natural Gradient for Deep Networks Razvan Pascanu, Yoshua Bengio
JMLR 2014 What Regularized Auto-Encoders Learn from the Data-Generating Distribution Guillaume Alain, Yoshua Bengio
ICLR 2013 1st International Conference on Learning Representations, ICLR 2013, Scottsdale, Arizona, USA, May 2-4, 2013, Conference Track Proceedings Yoshua Bengio, Yann LeCun
ICLR 2013 1st International Conference on Learning Representations, ICLR 2013, Scottsdale, Arizona, USA, May 2-4, 2013, Workshop Track Proceedings Yoshua Bengio, Yann LeCun
ICLR 2013 A Semantic Matching Energy Function for Learning with Multi-Relational Data Xavier Glorot, Antoine Bordes, Jason Weston, Yoshua Bengio
ICML 2013 Better Mixing via Deep Representations Yoshua Bengio, Gregoire Mesnil, Yann Dauphin, Salah Rifai
ICLR 2013 Big Neural Networks Waste Capacity Yann N. Dauphin, Yoshua Bengio
NeurIPS 2013 Generalized Denoising Auto-Encoders as Generative Models Yoshua Bengio, Li Yao, Guillaume Alain, Pascal Vincent
ICLR 2013 Joint Training Deep Boltzmann Machines for Classification Ian J. Goodfellow, Aaron C. Courville, Yoshua Bengio
ICLR 2013 Knowledge Matters: Importance of Prior Information for Optimization Çaglar Gülçehre, Yoshua Bengio
ICML 2013 Maxout Networks Ian Goodfellow, David Warde-Farley, Mehdi Mirza, Aaron Courville, Yoshua Bengio
ICLR 2013 Metric-Free Natural Gradient for Joint-Training of Boltzmann Machines Guillaume Desjardins, Razvan Pascanu, Aaron C. Courville, Yoshua Bengio
NeurIPS 2013 Multi-Prediction Deep Boltzmann Machines Ian Goodfellow, Mehdi Mirza, Aaron Courville, Yoshua Bengio
ICLR 2013 Natural Gradient Revisited Razvan Pascanu, Yoshua Bengio
ICML 2013 On the Difficulty of Training Recurrent Neural Networks Razvan Pascanu, Tomas Mikolov, Yoshua Bengio
ICLR 2013 Regularized Auto-Encoders Estimate Local Statistics Guillaume Alain, Yoshua Bengio, Salah Rifai
NeurIPS 2013 Stochastic Ratio Matching of RBMs for Sparse High-Dimensional Inputs Yann Dauphin, Yoshua Bengio
AISTATS 2013 Texture Modeling with Convolutional Spike-and-Slab RBMs and Deep Extensions Heng Luo, Pierre Luc Carrier, Aaron C. Courville, Yoshua Bengio
ICML 2012 A Generative Process for Contractive Auto-Encoders Salah Rifai, Yann N. Dauphin, Pascal Vincent, Yoshua Bengio
ECCV 2012 Disentangling Factors of Variation for Facial Expression Recognition Salah Rifai, Yoshua Bengio, Aaron C. Courville, Pascal Vincent, Mehdi Mirza
AISTATS 2012 Joint Learning of Words and Meaning Representations for Open-Text Semantic Parsing Antoine Bordes, Xavier Glorot, Jason Weston, Yoshua Bengio
ICML 2012 Large-Scale Feature Learning with Spike-and-Slab Sparse Coding Ian J. Goodfellow, Aaron C. Courville, Yoshua Bengio
JMLR 2012 Learning Algorithms for the Classification Restricted Boltzmann Machine Hugo Larochelle, Michael Mandel, Razvan Pascanu, Yoshua Bengio
ICML 2012 Modeling Temporal Dependencies in High-Dimensional Sequences: Application to Polyphonic Music Generation and Transcription Nicolas Boulanger-Lewandowski, Yoshua Bengio, Pascal Vincent
JMLR 2012 Random Search for Hyper-Parameter Optimization James Bergstra, Yoshua Bengio
AISTATS 2011 A Spike and Slab Restricted Boltzmann Machine Aaron Courville, James Bergstra, Yoshua Bengio
NeurIPS 2011 Algorithms for Hyper-Parameter Optimization James S. Bergstra, Rémi Bardenet, Yoshua Bengio, Balázs Kégl
ICML 2011 Contractive Auto-Encoders: Explicit Invariance During Feature Extraction Salah Rifai, Pascal Vincent, Xavier Muller, Xavier Glorot, Yoshua Bengio
AISTATS 2011 Deep Learners Benefit More from Out-of-Distribution Examples Yoshua Bengio, Frédéric Bastien, Arnaud Bergeron, Nicolas Boulanger–Lewandowski, Thomas Breuel, Youssouf Chherawala, Moustapha Cisse, Myriam Côté, Dumitru Erhan, Jeremy Eustache, Xavier Glorot, Xavier Muller, Sylvain Pannetier Lebeuf, Razvan Pascanu, Salah Rifai, François Savard, Guillaume Sicard
AISTATS 2011 Deep Sparse Rectifier Neural Networks Xavier Glorot, Antoine Bordes, Yoshua Bengio
AISTATS 2011 Discussion of “The Neural Autoregressive Distribution Estimator” Yoshua Bengio
ICML 2011 Domain Adaptation for Large-Scale Sentiment Classification: A Deep Learning Approach Xavier Glorot, Antoine Bordes, Yoshua Bengio
ECML-PKDD 2011 Higher Order Contractive Auto-Encoder Salah Rifai, Grégoire Mesnil, Pascal Vincent, Xavier Muller, Yoshua Bengio, Yann N. Dauphin, Xavier Glorot
ICML 2011 Large-Scale Learning of Embeddings with Reconstruction Sampling Yann N. Dauphin, Xavier Glorot, Yoshua Bengio
AAAI 2011 Learning Structured Embeddings of Knowledge Bases Antoine Bordes, Jason Weston, Ronan Collobert, Yoshua Bengio
NeurIPS 2011 On Tracking the Partition Function Guillaume Desjardins, Yoshua Bengio, Aaron C. Courville
ALT 2011 On the Expressive Power of Deep Architectures Yoshua Bengio, Olivier Delalleau
NeurIPS 2011 Shallow vs. Deep Sum-Product Networks Olivier Delalleau, Yoshua Bengio
NeurIPS 2011 The Manifold Tangent Classifier Salah Rifai, Yann N. Dauphin, Pascal Vincent, Yoshua Bengio, Xavier Muller
ICML 2011 Unsupervised Models of Images by Spikeand-Slab RBMs Aaron C. Courville, James Bergstra, Yoshua Bengio
JMLR 2010 Stacked Denoising Autoencoders: Learning Useful Representations in a Deep Network with a Local Denoising Criterion Pascal Vincent, Hugo Larochelle, Isabelle Lajoie, Yoshua Bengio, Pierre-Antoine Manzagol
AISTATS 2010 Tempered Markov Chain Monte Carlo for Training of Restricted Boltzmann Machines Guillaume Desjardins, Aaron Courville, Yoshua Bengio, Pascal Vincent, Olivier Delalleau
AISTATS 2010 Understanding the Difficulty of Training Deep Feedforward Neural Networks Xavier Glorot, Yoshua Bengio
JMLR 2010 Why Does Unsupervised Pre-Training Help Deep Learning? Dumitru Erhan, Yoshua Bengio, Aaron Courville, Pierre-Antoine Manzagol, Pascal Vincent, Samy Bengio
AISTATS 2010 Why Does Unsupervised Pre-Training Help Deep Learning? Dumitru Erhan, Aaron Courville, Yoshua Bengio, Pascal Vincent
NeurIPS 2009 An Infinite Factor Model Hierarchy via a Noisy-or Mechanism Douglas Eck, Yoshua Bengio, Aaron C. Courville
ICML 2009 Curriculum Learning Yoshua Bengio, Jérôme Louradour, Ronan Collobert, Jason Weston
JMLR 2009 Exploring Strategies for Training Deep Neural Networks Hugo Larochelle, Yoshua Bengio, Jérôme Louradour, Pascal Lamblin
JMLR 2009 Incorporating Functional Knowledge in Neural Networks Charles Dugas, Yoshua Bengio, François Bélisle, Claude Nadeau, René Garcia
FnTML 2009 Learning Deep Architectures for AI Yoshua Bengio
NeurIPS 2009 Slow, Decorrelated Features for Pretraining Complex Cell-like Networks Yoshua Bengio, James S. Bergstra
AISTATS 2009 The Difficulty of Training Deep Architectures and the Effect of Unsupervised Pre-Training Dumitru Erhan, Pierre-Antoine Manzagol, Yoshua Bengio, Samy Bengio, Pascal Vincent
ICML 2009 Workshop Summary: Workshop on Learning Feature Hierarchies Kai Yu, Ruslan Salakhutdinov, Yann LeCun, Geoffrey E. Hinton, Yoshua Bengio
ICML 2008 Classification Using Discriminative Restricted Boltzmann Machines Hugo Larochelle, Yoshua Bengio
ICML 2008 Extracting and Composing Robust Features with Denoising Autoencoders Pascal Vincent, Hugo Larochelle, Yoshua Bengio, Pierre-Antoine Manzagol
AAAI 2008 Zero-Data Learning of New Tasks Hugo Larochelle, Dumitru Erhan, Yoshua Bengio
AISTATS 2007 A Hybrid Pareto Model for Conditional Density Estimation of Asymmetric Fat-Tail Data Julie Carreau, Yoshua Bengio
ICML 2007 An Empirical Evaluation of Deep Architectures on Problems with Many Factors of Variation Hugo Larochelle, Dumitru Erhan, Aaron C. Courville, James Bergstra, Yoshua Bengio
NeurIPS 2007 Augmented Functional Time Series Representation and Forecasting with Gaussian Processes Nicolas Chapados, Yoshua Bengio
AISTATS 2007 Continuous Neural Networks Nicolas Le Roux, Yoshua Bengio
NeurIPS 2007 Learning the 2-D Topology of Images Nicolas L. Roux, Yoshua Bengio, Pascal Lamblin, Marc Joliveau, Balázs Kégl
NeurIPS 2007 Topmoumoute Online Natural Gradient Algorithm Nicolas L. Roux, Pierre-antoine Manzagol, Yoshua Bengio
NeurIPS 2006 Greedy Layer-Wise Training of Deep Networks Yoshua Bengio, Pascal Lamblin, Dan Popovici, Hugo Larochelle
NeurIPS 2005 Convex Neural Networks Yoshua Bengio, Nicolas L. Roux, Pascal Vincent, Olivier Delalleau, Patrice Marcotte
AISTATS 2005 Efficient Non-Parametric Function Induction in Semi-Supervised Learning Olivier Delalleau, Yoshua Bengio, Nicolas Le Roux
AISTATS 2005 Greedy Spectral Embedding Marie Ouimet, Yoshua Bengio
AISTATS 2005 Hierarchical Probabilistic Neural Network Language Model Frederic Morin, Yoshua Bengio
NeurIPS 2005 Non-Local Manifold Parzen Windows Yoshua Bengio, Hugo Larochelle, Pascal Vincent
NeurIPS 2005 The Curse of Highly Variable Functions for Local Kernel Machines Yoshua Bengio, Olivier Delalleau, Nicolas L. Roux
NeurIPS 2004 Brain Inspired Reinforcement Learning Françcois Rivest, Yoshua Bengio, John Kalaska
NeCo 2004 Learning Eigenfunctions Links Spectral Embedding and Kernel PCA Yoshua Bengio, Olivier Delalleau, Nicolas Le Roux, Jean-François Paiement, Pascal Vincent, Marie Ouimet
JMLR 2004 No Unbiased Estimator of the Variance of K-Fold Cross-Validation Yoshua Bengio, Yves Grandvalet
NeurIPS 2004 Non-Local Manifold Tangent Learning Yoshua Bengio, Martin Monperrus
NeurIPS 2004 Semi-Supervised Learning by Entropy Minimization Yves Grandvalet, Yoshua Bengio
MLJ 2003 Inference for the Generalization Error Claude Nadeau, Yoshua Bengio
NeurIPS 2003 No Unbiased Estimator of the Variance of K-Fold Cross-Validation Yoshua Bengio, Yves Grandvalet
NeurIPS 2003 Out-of-Sample Extensions for LLE, Isomap, MDS, Eigenmaps, and Spectral Clustering Yoshua Bengio, Jean-françcois Paiement, Pascal Vincent, Olivier Delalleau, Nicolas L. Roux, Marie Ouimet
AISTATS 2003 Quick Training of Probabilistic Neural Nets by Importance Sampling Yoshua Bengio, Jean-Sébastien Senecal
NeCo 2002 A Parallel Mixture of SVMs for Very Large Scale Problems Ronan Collobert, Samy Bengio, Yoshua Bengio
MLJ 2002 Guest Introduction: Special Issue on New Methods for Model Selection and Model Combination Yoshua Bengio, Dale Schuurmans
MLJ 2002 Kernel Matching Pursuit Pascal Vincent, Yoshua Bengio
NeurIPS 2002 Manifold Parzen Windows Pascal Vincent, Yoshua Bengio
MLJ 2002 Model Selection for Small Sample Regression Olivier Chapelle, Vladimir Vapnik, Yoshua Bengio
NeCo 2002 Robust Regression with Asymmetric Heavy-Tail Noise Distributions Ichiro Takeuchi, Yoshua Bengio, Takafumi Kanamori
NeurIPS 2001 A Parallel Mixture of SVMs for Very Large Scale Problems Ronan Collobert, Samy Bengio, Yoshua Bengio
NeurIPS 2001 Estimating Car Insurance Premia: A Case Study in High-Dimensional Data Inference Nicolas Chapados, Yoshua Bengio, Pascal Vincent, Joumana Ghosn, Charles Dugas, Ichiro Takeuchi, Linyan Meng
NeurIPS 2001 K-Local Hyperplane and Convex Distance Nearest Neighbor Algorithms Pascal Vincent, Yoshua Bengio
NeurIPS 2000 A Neural Probabilistic Language Model Yoshua Bengio, Réjean Ducharme, Pascal Vincent
NeCo 2000 Boosting Neural Networks Holger Schwenk, Yoshua Bengio
NeCo 2000 Gradient-Based Optimization of Hyperparameters Yoshua Bengio
NeurIPS 2000 Incorporating Second-Order Functional Knowledge for Better Option Pricing Charles Dugas, Yoshua Bengio, François Bélisle, Claude Nadeau, René Garcia
NeurIPS 1999 Inference for the Generalization Error Claude Nadeau, Yoshua Bengio
NeurIPS 1999 Modeling High-Dimensional Discrete Data with Multi-Layer Neural Networks Yoshua Bengio, Samy Bengio
NeCo 1999 Stochastic Learning of Strategic Equilibria for Auctions Samy Bengio, Yoshua Bengio, Jacques Robert, Gilles Bélanger
CVPR 1997 Global Training of Document Processing Systems Using Graph Transformer Networks Léon Bottou, Yoshua Bengio, Yann LeCun
NeurIPS 1997 Shared Context Probabilistic Transducers Yoshua Bengio, Samy Bengio, Jean-Franc Isabelle, Yoram Singer
NeurIPS 1997 Training Methods for Adaptive Boosting of Neural Networks Holger Schwenk, Yoshua Bengio
NeurIPS 1996 Multi-Task Learning for Stock Selection Joumana Ghosn, Yoshua Bengio
JAIR 1995 Diffusion of Context and Credit Information in Markovian Models Yoshua Bengio, Paolo Frasconi
NeurIPS 1995 Hierarchical Recurrent Neural Networks for Long-Term Dependencies Salah El Hihi, Yoshua Bengio
NeCo 1995 LeRec: A NN/HMM Hybrid for On-Line Handwriting Recognition Yoshua Bengio, Yann LeCun, Craig R. Nohl, Christopher J. C. Burges
NeurIPS 1995 Recurrent Neural Networks for Missing or Asynchronous Data Yoshua Bengio, Francois Gingras
NeurIPS 1994 An Input Output HMM Architecture Yoshua Bengio, Paolo Frasconi
NeurIPS 1994 Convergence Properties of the K-Means Algorithms Léon Bottou, Yoshua Bengio
NeurIPS 1994 Diffusion of Credit in Markovian Models Yoshua Bengio, Paolo Frasconi
NeurIPS 1993 Credit Assignment Through Time: Alternatives to Backpropagation Yoshua Bengio, Paolo Frasconi
NeurIPS 1993 Globally Trained Handwritten Word Recognizer Using Spatial Representation, Convolutional Neural Networks, and Hidden Markov Models Yoshua Bengio, Yann LeCun, Donnie Henderson
NeurIPS 1991 Neural Network - Gaussian Mixture Hybrid for Speech Recognition or Density Estimation Yoshua Bengio, Renato De Mori, Giovanni Flammia, Ralf Kompe
NeurIPS 1989 A Neural Network to Detect Homologies in Proteins Yoshua Bengio, Samy Bengio, Yannick Pouliot, Patrick Agin
IJCAI 1989 On the Generalization Capability of Multi-Layered Networks in the Extraction of Speech Properties Renato de Mori, Yoshua Bengio, Piero Cosi
NeurIPS 1989 Speaker Independent Speech Recognition with Neural Networks and Speech Knowledge Yoshua Bengio, Renato de Mori, Régis Cardin
AAAI 1988 Data-Driven Execution of Multi-Layered Networks for Automatic Speech Recognition Renato de Mori, Yoshua Bengio, Régis Cardin
NeurIPS 1988 Use of Multi-Layered Networks for Coding Speech with Phonetic Features Yoshua Bengio, Régis Cardin, Renato de Mori, Piero Cosi