Emmanuel Bengio

According to our database, Emmanuel Bengio authored at least 26 papers between 2013 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2024

Investigating Generalization Behaviours of Generative Flow Networks.

Lazar Atanackovic, Emmanuel Bengio

CoRR, 2024

QGFN: Controllable Greediness with Action Values.

Elaine Lau, Stephen Zhewen Lu, Ling Pan, Doina Precup, Emmanuel Bengio

CoRR, 2024

2023

GFlowNet Foundations.

Yoshua Bengio, Salem Lahlou, Tristan Deleu, Edward J. Hu, Mo Tiwari, Emmanuel Bengio

J. Mach. Learn. Res., 2023

Maximum entropy GFlowNets with soft Q-learning.

Sobhan Mohammadpour, Emmanuel Bengio, Emma Frejinger, Pierre-Luc Bacon

CoRR, 2023

DGFN: Double Generative Flow Networks.

Elaine Lau, Nikhil Vemgal, Doina Precup, Emmanuel Bengio

CoRR, 2023

Local Search GFlowNets.

Minsu Kim, Taeyoung Yun, Emmanuel Bengio, Dinghuai Zhang, Yoshua Bengio, Sungsoo Ahn, Jinkyoo Park

CoRR, 2023

Goal-conditioned GFlowNets for Controllable Multi-Objective Molecular Design.

Julien Roy, Pierre-Luc Bacon, Christopher Pal, Emmanuel Bengio

CoRR, 2023

Towards Understanding and Improving GFlowNet Training.

Max W. Shen, Emmanuel Bengio, Ehsan Hajiramezanali, Andreas Loukas, Kyunghyun Cho, Tommaso Biancalani

Proceedings of the International Conference on Machine Learning, 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

Proceedings of the International Conference on Machine Learning, 2023

Multi-Objective GFlowNets.

Moksh Jain, Sharath Chandra Raparthy, Alex Hernández-García, Jarrid Rector-Brooks, Yoshua Bengio, Santiago Miret, Emmanuel Bengio

Proceedings of the International Conference on Machine Learning, 2023

2022

Trajectory balance: Improved credit assignment in GFlowNets.

Nikolay Malkin, Moksh Jain, Emmanuel Bengio, Chen Sun, Yoshua Bengio

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Biological Sequence Design with GFlowNets.

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

Proceedings of the International Conference on Machine Learning, 2022

2021

Correcting Momentum in Temporal Difference Learning.

Emmanuel Bengio, Joelle Pineau, Doina Precup

CoRR, 2021

Flow Network based Generative Models for Non-Iterative Diverse Candidate Generation.

Emmanuel Bengio, Moksh Jain, Maksym Korablyov, Doina Precup, Yoshua Bengio

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

TDprop: Does Adaptive Optimization With Jacobi Preconditioning Help Temporal Difference Learning?

Joshua Romoff, Peter Henderson, David Kanaa, Emmanuel Bengio, Ahmed Touati, Pierre-Luc Bacon, Joelle Pineau

Proceedings of the AAMAS '21: 20th International Conference on Autonomous Agents and Multiagent Systems, 2021

2020

TDprop: Does Jacobi Preconditioning Help Temporal Difference Learning?

Joshua Romoff, Peter Henderson, David Kanaa, Emmanuel Bengio, Ahmed Touati, Pierre-Luc Bacon, Joelle Pineau

CoRR, 2020

Interference and Generalization in Temporal Difference Learning.

Emmanuel Bengio, Joelle Pineau, Doina Precup

Proceedings of the 37th International Conference on Machine Learning, 2020

2018

Fooling the classifier: Ligand antagonism and adversarial examples.

Thomas J. Rademaker, Emmanuel Bengio, Paul François

CoRR, 2018

Disentangling the independently controllable factors of variation by interacting with the world.

Valentin Thomas, Emmanuel Bengio, William Fedus, Jules Pondard, Philippe Beaudoin, Hugo Larochelle, Joelle Pineau, Doina Precup, Yoshua Bengio

CoRR, 2018

2017

Independently Controllable Factors.

Valentin Thomas, Jules Pondard, Emmanuel Bengio, Marc Sarfati, Philippe Beaudoin, Marie-Jean Meurs, Joelle Pineau, Doina Precup, Yoshua Bengio

CoRR, 2017

Independently Controllable Features.

Emmanuel Bengio, Valentin Thomas, Joelle Pineau, Doina Precup, Yoshua Bengio

CoRR, 2017

A Closer Look at Memorization in Deep Networks.

Devansh Arpit, Stanislaw Jastrzebski, Nicolas Ballas, David Krueger, Emmanuel Bengio, Maxinder S. Kanwal, Tegan Maharaj, Asja Fischer, Aaron C. Courville, Yoshua Bengio, Simon Lacoste-Julien

Proceedings of the 34th International Conference on Machine Learning, 2017

Deep Nets Don't Learn via Memorization.

David Krueger, Nicolas Ballas, Stanislaw Jastrzebski, Devansh Arpit, Maxinder S. Kanwal, Tegan Maharaj, Emmanuel Bengio, Asja Fischer, Aaron C. Courville

Proceedings of the 5th International Conference on Learning Representations, 2017

World Knowledge for Reading Comprehension: Rare Entity Prediction with Hierarchical LSTMs Using External Descriptions.

Teng Long, Emmanuel Bengio, Ryan Lowe, Jackie Chi Kit Cheung, Doina Precup

Proceedings of the 2017 Conference on Empirical Methods in Natural Language Processing, 2017

2015

Conditional Computation in Neural Networks for faster models.

Emmanuel Bengio, Pierre-Luc Bacon, Joelle Pineau, Doina Precup

CoRR, 2015

2013

Combining modality specific deep neural networks for emotion recognition in video.

Samira Ebrahimi Kahou, Christopher J. Pal, Xavier Bouthillier, Pierre Froumenty, Çaglar Gülçehre, Roland Memisevic, Pascal Vincent, Aaron C. Courville, Yoshua Bengio, Raul Chandias Ferrari, Mehdi Mirza, Sébastien Jean, Pierre Luc Carrier, Yann N. Dauphin, Nicolas Boulanger-Lewandowski, Abhishek Aggarwal, Jeremie Zumer, Pascal Lamblin, Jean-Philippe Raymond, Guillaume Desjardins, Razvan Pascanu, David Warde-Farley, Atousa Torabi, Arjun Sharma, Emmanuel Bengio, Kishore Reddy Konda, Zhenzhou Wu

Proceedings of the 2013 International Conference on Multimodal Interaction, 2013