Olivier Pietquin

ORCID

Publication Activity (10 Years)

Years Active: 2002-2024
Publications (10 Years): 157

Top Venues

Publications

Mathieu Rita, Florian Strub, Rahma Chaabouni, Paul Michel, Emmanuel Dupoux, Olivier Pietquin
Countering Reward Over-Optimization in LLM with Demonstration-Guided Reinforcement Learning. ACL (Findings) (2024)
Yannis Flet-Berliac, Nathan Grinsztajn, Florian Strub, Eugene Choi, Chris Cremer, Arash Ahmadian, Yash Chandak, Mohammad Gheshlaghi Azar, Olivier Pietquin, Matthieu Geist
Contrastive Policy Gradient: Aligning LLMs on sequence-level scores in a supervised-friendly fashion. CoRR (2024)
Kai Cui, Gökçe Dayanikli, Mathieu Laurière, Matthieu Geist, Olivier Pietquin, Heinz Koeppl
Learning Discrete-Time Major-Minor Mean Field Games. AAAI (2024)
Arash Ahmadian, Chris Cremer, Matthias Gallé, Marzieh Fadaee, Julia Kreutzer, Olivier Pietquin, Ahmet Üstün, Sara Hooker
Back to Basics: Revisiting REINFORCE Style Optimization for Learning from Human Feedback in LLMs. CoRR (2024)
Nathan Grinsztajn, Yannis Flet-Berliac, Mohammad Gheshlaghi Azar, Florian Strub, Bill Wu, Eugene Choi, Chris Cremer, Arash Ahmadian, Yash Chandak, Olivier Pietquin, Matthieu Geist
Averaging log-likelihoods in direct alignment. CoRR (2024)
Eugene Choi, Arash Ahmadian, Matthieu Geist, Olivier Pietquin, Mohammad Gheshlaghi Azar
Self-Improving Robust Preference Optimization. CoRR (2024)
Zida Wu, Mathieu Laurière, Samuel Jia Cong Chua, Matthieu Geist, Olivier Pietquin, Ankur Mehta
Population-aware Online Mirror Descent for Mean-Field Games by Deep Reinforcement Learning. AAMAS (2024)
Geoffrey Cideron, Sertan Girgin, Mauro Verzetti, Damien Vincent, Matej Kastelic, Zalán Borsos, Brian McWilliams, Victor Ungureanu, Olivier Bachem, Olivier Pietquin, Matthieu Geist, Léonard Hussenot, Neil Zeghidour, Andrea Agostinelli
MusicRL: Aligning Music Generation to Human Preferences. CoRR (2024)
Mathieu Rita, Paul Michel, Rahma Chaabouni, Olivier Pietquin, Emmanuel Dupoux, Florian Strub
Language Evolution with Deep Learning. CoRR (2024)
Zida Wu, Mathieu Laurière, Samuel Jia Cong Chua, Matthieu Geist, Olivier Pietquin, Ankur Mehta
Population-aware Online Mirror Descent for Mean-Field Games by Deep Reinforcement Learning. CoRR (2024)
Arash Ahmadian, Chris Cremer, Matthias Gallé, Marzieh Fadaee, Julia Kreutzer, Olivier Pietquin, Ahmet Üstün, Sara Hooker
Back to Basics: Revisiting REINFORCE-Style Optimization for Learning from Human Feedback in LLMs. ACL (1) (2024)
Mathieu Rita, Florian Strub, Rahma Chaabouni, Paul Michel, Emmanuel Dupoux, Olivier Pietquin
Countering Reward Over-optimization in LLM with Demonstration-Guided Reinforcement Learning. CoRR (2024)
Zalán Borsos, Raphaël Marinier, Damien Vincent, Eugene Kharitonov, Olivier Pietquin, Matthew Sharifi, Dominik Roblek, Olivier Teboul, David Grangier, Marco Tagliasacchi, Neil Zeghidour
AudioLM: A Language Modeling Approach to Audio Generation. IEEE ACM Trans. Audio Speech Lang. Process. 31 (2023)
Geoffrey Cideron, Baruch Tabanpour, Sebastian Curi, Sertan Girgin, Léonard Hussenot, Gabriel Dulac-Arnold, Matthieu Geist, Olivier Pietquin, Robert Dadashi
Get Back Here: Robust Imitation by Return-to-Distribution Planning. CoRR (2023)
Kai Cui, Gökçe Dayanikli, Mathieu Laurière, Matthieu Geist, Olivier Pietquin, Heinz Koeppl
Learning Discrete-Time Major-Minor Mean Field Games. CoRR (2023)
Giorgia Ramponi, Pavel Kolev, Olivier Pietquin, Niao He, Mathieu Laurière, Matthieu Geist
On Imitation in Mean-field Games. CoRR (2023)
Eugene Kharitonov, Damien Vincent, Zalán Borsos, Raphaël Marinier, Sertan Girgin, Olivier Pietquin, Matthew Sharifi, Marco Tagliasacchi, Neil Zeghidour
Speak, Read and Prompt: High-Fidelity Text-to-Speech with Minimal Supervision. CoRR (2023)
Chris Donahue, Antoine Caillon, Adam Roberts, Ethan Manilow, Philippe Esling, Andrea Agostinelli, Mauro Verzetti, Ian Simon, Olivier Pietquin, Neil Zeghidour, Jesse H. Engel
SingSong: Generating musical accompaniments from singing. CoRR (2023)
Eugene Kharitonov, Damien Vincent, Zalán Borsos, Raphaël Marinier, Sertan Girgin, Olivier Pietquin, Matt Sharifi, Marco Tagliasacchi, Neil Zeghidour
Speak, Read and Prompt: High-Fidelity Text-to-Speech with Minimal Supervision. Trans. Assoc. Comput. Linguistics 11 (2023)
Paul Roit, Johan Ferret, Lior Shani, Roee Aharoni, Geoffrey Cideron, Robert Dadashi, Matthieu Geist, Sertan Girgin, Léonard Hussenot, Orgad Keller, Nikola Momchev, Sabela Ramos, Piotr Stanczyk, Nino Vieillard, Olivier Bachem, Gal Elidan, Avinatan Hassidim, Olivier Pietquin, Idan Szpektor
Factually Consistent Summarization via Reinforcement Learning with Textual Entailment Feedback. CoRR (2023)
Toshinori Kitamura, Tadashi Kozuno, Yunhao Tang, Nino Vieillard, Michal Valko, Wenhao Yang, Jincheng Mei, Pierre Ménard, Mohammad Gheshlaghi Azar, Rémi Munos, Olivier Pietquin, Matthieu Geist, Csaba Szepesvári, Wataru Kumagai, Yutaka Matsuo
Regularization and Variance-Weighted Regression Achieves Minimax Optimality in Linear MDPs: Theory and Practice. CoRR (2023)
Giorgia Ramponi, Pavel Kolev, Olivier Pietquin, Niao He, Mathieu Laurière, Matthieu Geist
On Imitation in Mean-field Games. NeurIPS (2023)
Toshinori Kitamura, Tadashi Kozuno, Yunhao Tang, Nino Vieillard, Michal Valko, Wenhao Yang, Jincheng Mei, Pierre Ménard, Mohammad Gheshlaghi Azar, Rémi Munos, Olivier Pietquin, Matthieu Geist, Csaba Szepesvári, Wataru Kumagai, Yutaka Matsuo
Regularization and Variance-Weighted Regression Achieves Minimax Optimality in Linear MDPs: Theory and Practice. ICML (2023)
Paul Roit, Johan Ferret, Lior Shani, Roee Aharoni, Geoffrey Cideron, Robert Dadashi, Matthieu Geist, Sertan Girgin, Léonard Hussenot, Orgad Keller, Nikola Momchev, Sabela Ramos Garea, Piotr Stanczyk, Nino Vieillard, Olivier Bachem, Gal Elidan, Avinatan Hassidim, Olivier Pietquin, Idan Szpektor
Factually Consistent Summarization via Reinforcement Learning with Textual Entailment Feedback. ACL (1) (2023)
Alexis Jacq, Manu Orsini, Gabriel Dulac-Arnold, Olivier Pietquin, Matthieu Geist, Olivier Bachem
C3PO: Learning to Achieve Arbitrary Goals via Massively Entropic Pretraining. CoRR (2022)
Mathieu Laurière, Sarah Perrin, Sertan Girgin, Paul Muller, Ayush Jain, Theophile Cabannes, Georgios Piliouras, Julien Pérolat, Romuald Élie, Olivier Pietquin, Matthieu Geist
Scalable Deep Reinforcement Learning Algorithms for Mean Field Games. CoRR (2022)
Shideh Rezaeifar, Robert Dadashi, Nino Vieillard, Léonard Hussenot, Olivier Bachem, Olivier Pietquin, Matthieu Geist
Offline Reinforcement Learning as Anti-exploration. AAAI (2022)
Mathieu Rita, Florian Strub, Jean-Bastien Grill, Olivier Pietquin, Emmanuel Dupoux
On the role of population heterogeneity in emergent communication. CoRR (2022)
Paul Muller, Mark Rowland, Romuald Elie, Georgios Piliouras, Julien Pérolat, Mathieu Laurière, Raphaël Marinier, Olivier Pietquin, Karl Tuyls
Learning Equilibria in Mean-Field Games: Introducing Mean-Field PSRO. AAMAS (2022)
Geoffrey Cideron, Sertan Girgin, Anton Raichuk, Olivier Pietquin, Olivier Bachem, Léonard Hussenot
vec2text with Round-Trip Translations. CoRR (2022)
Mathieu Laurière, Sarah Perrin, Sertan Girgin, Paul Muller, Ayush Jain, Theophile Cabannes, Georgios Piliouras, Julien Pérolat, Romuald Elie, Olivier Pietquin, Matthieu Geist
Scalable Deep Reinforcement Learning Algorithms for Mean Field Games. ICML (2022)
Robert Dadashi, Léonard Hussenot, Damien Vincent, Sertan Girgin, Anton Raichuk, Matthieu Geist, Olivier Pietquin
Continuous Control with Action Quantization from Demonstrations. ICML (2022)
Alexis Jacq, Johan Ferret, Olivier Pietquin, Matthieu Geist
Lazy-MDPs: Towards Interpretable RL by Learning When to Act. AAMAS (2022)
Mathieu Rita, Corentin Tallec, Paul Michel, Jean-Bastien Grill, Olivier Pietquin, Emmanuel Dupoux, Florian Strub
Emergent Communication: Generalization and Overfitting in Lewis Games. NeurIPS (2022)
Julien Pérolat, Sarah Perrin, Romuald Elie, Mathieu Laurière, Georgios Piliouras, Matthieu Geist, Karl Tuyls, Olivier Pietquin
Scaling Mean Field Games by Online Mirror Descent. AAMAS (2022)
Matthieu Geist, Julien Pérolat, Mathieu Laurière, Romuald Elie, Sarah Perrin, Olivier Bachem, Rémi Munos, Olivier Pietquin
Concave Utility Reinforcement Learning: The Mean-field Game Viewpoint. AAMAS (2022)
Tadashi Kozuno, Wenhao Yang, Nino Vieillard, Toshinori Kitamura, Yunhao Tang, Jincheng Mei, Pierre Ménard, Mohammad Gheshlaghi Azar, Michal Valko, Rémi Munos, Olivier Pietquin, Matthieu Geist, Csaba Szepesvári
KL-Entropy-Regularized RL with a Generative Model is Minimax Optimal. CoRR (2022)
Mathieu Laurière, Sarah Perrin, Matthieu Geist, Olivier Pietquin
Learning Mean Field Games: A Survey. CoRR (2022)
Nino Vieillard, Marcin Andrychowicz, Anton Raichuk, Olivier Pietquin, Matthieu Geist
Implicitly Regularized RL with Implicit Q-values. AISTATS (2022)
Mathieu Rita, Florian Strub, Jean-Bastien Grill, Olivier Pietquin, Emmanuel Dupoux
On the role of population heterogeneity in emergent communication. ICLR (2022)
Theophile Cabannes, Mathieu Laurière, Julien Pérolat, Raphaël Marinier, Sertan Girgin, Sarah Perrin, Olivier Pietquin, Alexandre M. Bayen, Eric Goubault, Romuald Elie
Solving N-Player Dynamic Routing Games with Congestion: A Mean-Field Approach. AAMAS (2022)
Sarah Perrin, Mathieu Laurière, Julien Pérolat, Romuald Élie, Matthieu Geist, Olivier Pietquin
Generalization in Mean Field Games by Learning Master Policies. AAAI (2022)
Alexis Jacq, Johan Ferret, Olivier Pietquin, Matthieu Geist
Lazy-MDPs: Towards Interpretable Reinforcement Learning by Learning When to Act. CoRR (2022)
Paul Muller, Romuald Elie, Mark Rowland, Mathieu Laurière, Julien Pérolat, Sarah Perrin, Matthieu Geist, Georgios Piliouras, Olivier Pietquin, Karl Tuyls
Learning Correlated Equilibria in Mean-Field Games. CoRR (2022)
Alice Martin, Guillaume Quispe, Charles Ollion, Sylvain Le Corff, Florian Strub, Olivier Pietquin
Learning Natural Language Generation with Truncated Reinforcement Learning. NAACL-HLT (2022)
Zalán Borsos, Raphaël Marinier, Damien Vincent, Eugene Kharitonov, Olivier Pietquin, Matthew Sharifi, Olivier Teboul, David Grangier, Marco Tagliasacchi, Neil Zeghidour
AudioLM: a Language Modeling Approach to Audio Generation. CoRR (2022)
Mathieu Rita, Corentin Tallec, Paul Michel, Jean-Bastien Grill, Olivier Pietquin, Emmanuel Dupoux, Florian Strub
Emergent Communication: Generalization and Overfitting in Lewis Games. CoRR (2022)
Nathan Grinsztajn, Johan Ferret, Olivier Pietquin, Philippe Preux, Matthieu Geist
There Is No Turning Back: A Self-Supervised Approach for Reversibility-Aware Reinforcement Learning. NeurIPS (2021)
Sarah Perrin, Mathieu Laurière, Julien Pérolat, Romuald Élie, Matthieu Geist, Olivier Pietquin
Generalization in Mean Field Games by Learning Master Policies. CoRR (2021)
Robert Dadashi, Shideh Rezaeifar, Nino Vieillard, Léonard Hussenot, Olivier Pietquin, Matthieu Geist
Offline Reinforcement Learning with Pseudometric Learning. CoRR (2021)
Paul Muller, Mark Rowland, Romuald Elie, Georgios Piliouras, Julien Pérolat, Mathieu Laurière, Raphaël Marinier, Olivier Pietquin, Karl Tuyls
Learning Equilibria in Mean-Field Games: Introducing Mean-Field PSRO. CoRR (2021)
Sarah Perrin, Mathieu Laurière, Julien Pérolat, Matthieu Geist, Romuald Élie, Olivier Pietquin
Mean Field Games Flock! The Reinforcement Learning Way. CoRR (2021)
Léonard Hussenot, Robert Dadashi, Matthieu Geist, Olivier Pietquin
Show Me the Way: Intrinsic Motivation from Demonstrations. AAMAS (2021)
Julien Pérolat, Sarah Perrin, Romuald Elie, Mathieu Laurière, Georgios Piliouras, Matthieu Geist, Karl Tuyls, Olivier Pietquin
Scaling up Mean Field Games with Online Mirror Descent. CoRR (2021)
Alice Martin Donati, Guillaume Quispe, Charles Ollion, Sylvain Le Corff, Florian Strub, Olivier Pietquin
Learning Natural Language Generation from Scratch. CoRR (2021)
Nino Vieillard, Marcin Andrychowicz, Anton Raichuk, Olivier Pietquin, Matthieu Geist
Implicitly Regularized RL with Implicit Q-Values. CoRR (2021)
Sabela Ramos, Sertan Girgin, Léonard Hussenot, Damien Vincent, Hanna Yakubovich, Daniel Toyama, Anita Gergely, Piotr Stanczyk, Raphaël Marinier, Jeremiah Harmsen, Olivier Pietquin, Nikola Momchev
RLDS: an Ecosystem to Generate, Share and Use Datasets in Reinforcement Learning. CoRR (2021)
Mathieu Seurin, Florian Strub, Philippe Preux, Olivier Pietquin
Don't Do What Doesn't Matter: Intrinsic Motivation with Action Usefulness. IJCAI (2021)
Robert Dadashi, Shideh Rezaeifar, Nino Vieillard, Léonard Hussenot, Olivier Pietquin, Matthieu Geist
Offline Reinforcement Learning with Pseudometric Learning. ICML (2021)
Johan Ferret, Olivier Pietquin, Matthieu Geist
Self-Imitation Advantage Learning. AAMAS (2021)
Theophile Cabannes, Mathieu Laurière, Julien Pérolat, Raphaël Marinier, Sertan Girgin, Sarah Perrin, Olivier Pietquin, Alexandre M. Bayen, Éric Goubault, Romuald Elie
Solving N-player dynamic routing games with congestion: a mean field approach. CoRR (2021)
Robert Dadashi, Léonard Hussenot, Damien Vincent, Sertan Girgin, Anton Raichuk, Matthieu Geist, Olivier Pietquin
Continuous Control with Action Quantization from Demonstrations. CoRR (2021)
Marcin Andrychowicz, Anton Raichuk, Piotr Stanczyk, Manu Orsini, Sertan Girgin, Raphaël Marinier, Léonard Hussenot, Matthieu Geist, Olivier Pietquin, Marcin Michalski, Sylvain Gelly, Olivier Bachem
What Matters for On-Policy Deep Actor-Critic Methods? A Large-Scale Study. ICLR (2021)
Matthieu Geist, Julien Pérolat, Mathieu Laurière, Romuald Elie, Sarah Perrin, Olivier Bachem, Rémi Munos, Olivier Pietquin
Concave Utility Reinforcement Learning: the Mean-field Game viewpoint. CoRR (2021)
Aaqib Saeed, David Grangier, Olivier Pietquin, Neil Zeghidour
Learning From Heterogeneous Eeg Signals with Differentiable Channel Reordering. ICASSP (2021)
Mathieu Seurin, Florian Strub, Philippe Preux, Olivier Pietquin
Don't Do What Doesn't Matter: Intrinsic Motivation with Action Usefulness. CoRR (2021)
Léonard Hussenot, Marcin Andrychowicz, Damien Vincent, Robert Dadashi, Anton Raichuk, Lukasz Stafiniak, Sertan Girgin, Raphaël Marinier, Nikola Momchev, Sabela Ramos, Manu Orsini, Olivier Bachem, Matthieu Geist, Olivier Pietquin
Hyperparameter Selection for Imitation Learning. CoRR (2021)
Yannis Flet-Berliac, Johan Ferret, Olivier Pietquin, Philippe Preux, Matthieu Geist
Adversarially Guided Actor-Critic. ICLR (2021)
Manu Orsini, Anton Raichuk, Léonard Hussenot, Damien Vincent, Robert Dadashi, Sertan Girgin, Matthieu Geist, Olivier Bachem, Olivier Pietquin, Marcin Andrychowicz
What Matters for Adversarial Imitation Learning? CoRR (2021)
Shideh Rezaeifar, Robert Dadashi, Nino Vieillard, Léonard Hussenot, Olivier Bachem, Olivier Pietquin, Matthieu Geist
Offline Reinforcement Learning as Anti-Exploration. CoRR (2021)
Sarah Perrin, Mathieu Laurière, Julien Pérolat, Matthieu Geist, Romuald Élie, Olivier Pietquin
Mean Field Games Flock! The Reinforcement Learning Way. IJCAI (2021)
Yannis Flet-Berliac, Johan Ferret, Olivier Pietquin, Philippe Preux, Matthieu Geist
Adversarially Guided Actor-Critic. CoRR (2021)
Nathan Grinsztajn, Johan Ferret, Olivier Pietquin, Philippe Preux, Matthieu Geist
There Is No Turning Back: A Self-Supervised Approach for Reversibility-Aware Reinforcement Learning. CoRR (2021)
Manu Orsini, Anton Raichuk, Léonard Hussenot, Damien Vincent, Robert Dadashi, Sertan Girgin, Matthieu Geist, Olivier Bachem, Olivier Pietquin, Marcin Andrychowicz
What Matters for Adversarial Imitation Learning? NeurIPS (2021)
Robert Dadashi, Léonard Hussenot, Matthieu Geist, Olivier Pietquin
Primal Wasserstein Imitation Learning. ICLR (2021)
Léonard Hussenot, Marcin Andrychowicz, Damien Vincent, Robert Dadashi, Anton Raichuk, Sabela Ramos, Nikola Momchev, Sertan Girgin, Raphaël Marinier, Lukasz Stafiniak, Manu Orsini, Olivier Bachem, Matthieu Geist, Olivier Pietquin
Hyperparameter Selection for Imitation Learning. ICML (2021)
Yuchen Lu, Soumye Singhal, Florian Strub, Olivier Pietquin, Aaron C. Courville
Countering Language Drift with Seeded Iterated Learning. CoRR (2020)
Mathieu Seurin, Florian Strub, Philippe Preux, Olivier Pietquin
A Machine of Few Words: Interactive Speaker Recognition with Reinforcement Learning. INTERSPEECH (2020)
Geoffrey Cideron, Mathieu Seurin, Florian Strub, Olivier Pietquin
HIGhER: Improving instruction following with Hindsight Generation for Experience Replay. SSCI (2020)
Nino Vieillard, Bruno Scherrer, Olivier Pietquin, Matthieu Geist
Momentum in Reinforcement Learning. AISTATS (2020)
Mathieu Seurin, Philippe Preux, Olivier Pietquin
"I'm Sorry Dave, I'm Afraid I Can't Do That" Deep Q-Learning from Forbidden Actions. IJCNN (2020)
Robert Dadashi, Léonard Hussenot, Matthieu Geist, Olivier Pietquin
Primal Wasserstein Imitation Learning. CoRR (2020)
Marcin Andrychowicz, Anton Raichuk, Piotr Stanczyk, Manu Orsini, Sertan Girgin, Raphaël Marinier, Léonard Hussenot, Matthieu Geist, Olivier Pietquin, Marcin Michalski, Sylvain Gelly, Olivier Bachem
What Matters In On-Policy Reinforcement Learning? A Large-Scale Empirical Study. CoRR (2020)
Nino Vieillard, Olivier Pietquin, Matthieu Geist
Munchausen Reinforcement Learning. CoRR (2020)
Nino Vieillard, Tadashi Kozuno, Bruno Scherrer, Olivier Pietquin, Rémi Munos, Matthieu Geist
Leverage the Average: an Analysis of Regularization in RL. CoRR (2020)
Yuchen Lu, Soumye Singhal, Florian Strub, Olivier Pietquin, Aaron C. Courville
Supervised Seeded Iterated Learning for Interactive Language Learning. EMNLP (1) (2020)
Aaqib Saeed, David Grangier, Olivier Pietquin, Neil Zeghidour
Learning from Heterogeneous EEG Signals with Differentiable Channel Reordering. CoRR (2020)
Sarah Perrin, Julien Pérolat, Mathieu Laurière, Matthieu Geist, Romuald Elie, Olivier Pietquin
Fictitious Play for Mean Field Games: Continuous Time Analysis and Applications. CoRR (2020)
Nino Vieillard, Tadashi Kozuno, Bruno Scherrer, Olivier Pietquin, Rémi Munos, Matthieu Geist
Leverage the Average: an Analysis of KL Regularization in Reinforcement Learning. NeurIPS (2020)
Nino Vieillard, Olivier Pietquin, Matthieu Geist
Munchausen Reinforcement Learning. NeurIPS (2020)
Yuchen Lu, Soumye Singhal, Florian Strub, Olivier Pietquin, Aaron C. Courville
Supervised Seeded Iterated Learning for Interactive Language Learning. CoRR (2020)
Johan Ferret, Olivier Pietquin, Matthieu Geist
Self-Imitation Advantage Learning. CoRR (2020)
Olivier Buffer, Olivier Pietquin, Paul Weng
Reinforcement Learning. CoRR (2020)
Yuchen Lu, Soumye Singhal, Florian Strub, Aaron C. Courville, Olivier Pietquin
Countering Language Drift with Seeded Iterated Learning. ICML (2020)
Nino Vieillard, Olivier Pietquin, Matthieu Geist
Deep Conservative Policy Iteration. AAAI (2020)
Sarah Perrin, Julien Pérolat, Mathieu Laurière, Matthieu Geist, Romuald Elie, Olivier Pietquin
Fictitious Play for Mean Field Games: Continuous Time Analysis and Applications. NeurIPS (2020)
Léonard Hussenot, Matthieu Geist, Olivier Pietquin
CopyCAT: : Taking Control of Neural Policies with Constant Attacks. AAMAS (2020)
Alexis Jacq, Julien Pérolat, Matthieu Geist, Olivier Pietquin
Foolproof Cooperative Learning. ACML (2020)
Romuald Elie, Julien Pérolat, Mathieu Laurière, Matthieu Geist, Olivier Pietquin
On the Convergence of Model Free Learning in Mean Field Games. AAAI (2020)
Léonard Hussenot, Robert Dadashi, Matthieu Geist, Olivier Pietquin
Show me the Way: Intrinsic Motivation from Demonstrations. CoRR (2020)

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Publication Activity (10 Years)

Top Topics

Top Venues

Olivier Pietquin