Emmanuel Bengio

Orcid: 0000-0002-3257-4661

According to our database¹, Emmanuel Bengio authored at least 37 papers between 2013 and 2024.

Collaborative distances:

Dijkstra number² of four.
Erdős number³ of four.

Timeline

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On csauthors.net:

Bibliography

2024

Efficient Biological Data Acquisition through Inference Set Design.

[BibT_eX]

[DOI]

CoRR, 2024

Action abstractions for amortized sampling.

[BibT_eX]

[DOI]

CoRR, 2024

Improved Off-policy Reinforcement Learning in Biological Sequence Design.

[BibT_eX]

[DOI]

Alex Hernández-García

Jinkyoo Park

CoRR, 2024

Adaptive teachers for amortized samplers.

[BibT_eX]

[DOI]

CoRR, 2024

GFlowNet Pretraining with Inexpensive Rewards.

[BibT_eX]

[DOI]

Mohit Pandey

Gopeshh Subbaraj

Emmanuel Bengio

CoRR, 2024

Baking Symmetry into GFlowNets.

[BibT_eX]

[DOI]

CoRR, 2024

Rectifying Reinforcement Learning for Reward Matching.

[BibT_eX]

[DOI]

CoRR, 2024

Amortizing intractable inference in diffusion models for vision, language, and control.

[BibT_eX]

[DOI]

CoRR, 2024

Generative Active Learning for the Search of Small-molecule Protein Binders.

[BibT_eX]

[DOI]

CoRR, 2024

SynFlowNet: Towards Molecule Design with Guaranteed Synthesis Pathways.

[BibT_eX]

[DOI]

CoRR, 2024

Investigating Generalization Behaviours of Generative Flow Networks.

[BibT_eX]

[DOI]

Lazar Atanackovic

Emmanuel Bengio

CoRR, 2024

QGFN: Controllable Greediness with Action Values.

[BibT_eX]

[DOI]

CoRR, 2024

Learning to Scale Logits for Temperature-Conditional GFlowNets.

[BibT_eX]

[DOI]

Proceedings of the Forty-first International Conference on Machine Learning, 2024

Local Search GFlowNets.

[BibT_eX]

[DOI]

Proceedings of the Twelfth International Conference on Learning Representations, 2024

Maximum entropy GFlowNets with soft Q-learning.

[BibT_eX]

[DOI]

Proceedings of the International Conference on Artificial Intelligence and Statistics, 2024

2023

GFlowNet Foundations.

[BibT_eX]

[DOI]

J. Mach. Learn. Res., 2023

DGFN: Double Generative Flow Networks.

[BibT_eX]

[DOI]

CoRR, 2023

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

[BibT_eX]

[DOI]

CoRR, 2023

Towards Understanding and Improving GFlowNet Training.

[BibT_eX]

[DOI]

Proceedings of the International Conference on Machine Learning, 2023

Learning GFlowNets From Partial Episodes For Improved Convergence And Stability.

[BibT_eX]

[DOI]

Proceedings of the International Conference on Machine Learning, 2023

Multi-Objective GFlowNets.

[BibT_eX]

[DOI]

Moksh Jain

Sharath Chandra Raparthy

Alex Hernández-García

Proceedings of the International Conference on Machine Learning, 2023

2022

Trajectory balance: Improved credit assignment in GFlowNets.

[BibT_eX]

[DOI]

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

Biological Sequence Design with GFlowNets.

[BibT_eX]

[DOI]

Moksh Jain

Emmanuel Bengio

Alex Hernández-García

Jarrid Rector-Brooks

Bonaventure F. P. Dossou

Proceedings of the International Conference on Machine Learning, 2022

2021

Correcting Momentum in Temporal Difference Learning.

[BibT_eX]

[DOI]

Emmanuel Bengio

Joelle Pineau

Doina Precup

CoRR, 2021

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

[BibT_eX]

[DOI]

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?

[BibT_eX]

[DOI]

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

2020

TDprop: Does Jacobi Preconditioning Help Temporal Difference Learning?

[BibT_eX]

[DOI]

CoRR, 2020

Interference and Generalization in Temporal Difference Learning.

[BibT_eX]

[DOI]

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.

[BibT_eX]

[DOI]

Thomas J. Rademaker

Emmanuel Bengio

Paul François

CoRR, 2018

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

[BibT_eX]

[DOI]

CoRR, 2018

2017

Independently Controllable Factors.

[BibT_eX]

[DOI]

CoRR, 2017

Independently Controllable Features.

[BibT_eX]

[DOI]

CoRR, 2017

A Closer Look at Memorization in Deep Networks.

[BibT_eX]

[DOI]

Devansh Arpit

Stanislaw Jastrzebski

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

Deep Nets Don't Learn via Memorization.

[BibT_eX]

[DOI]

David Krueger

Nicolas Ballas

Stanislaw Jastrzebski

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

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

[BibT_eX]

[DOI]

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.

[BibT_eX]

[DOI]

CoRR, 2015

2013

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

[BibT_eX]

[DOI]

Proceedings of the 2013 International Conference on Multimodal Interaction, 2013

Emmanuel Bengio

Timeline

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