Unbiasing Truncated Backpropagation Through Time. - Corentin Tallec; Yann Ollivier (CoRR, 2017)

Unbiased Online Recurrent Optimization. - Corentin Tallec; Yann Ollivier (ICLR (Poster), 2018)

Can recurrent neural networks warp time? - Corentin Tallec; Yann Ollivier (ICLR (Poster), 2018)

Mixed batches and symmetric discriminators for GAN training. - Thomas Lucas 002; Corentin Tallec; Yann Ollivier; Jakob Verbeek (ICML, 2018)

Making Deep Q-learning methods robust to time discretization. - Corentin Tallec; Léonard Blier; Yann Ollivier (ICML, 2019)

Recurrent Neural Networks and Reinforcement Learning: Dynamic Approaches. (Réseaux Récurrents et Apprentissage par Renforcement: Approches Dynamiques). - Corentin Tallec (2019)

Bootstrap Your Own Latent - A New Approach to Self-Supervised Learning. - Jean-Bastien Grill; Florian Strub; Florent Altché; Corentin Tallec; Pierre H. Richemond; Elena Buchatskaya; Carl Doersch; Bernardo Ávila Pires; Zhaohan Guo; Mohammad Gheshlaghi Azar; Bilal Piot; Koray Kavukcuoglu; et al. (NeurIPS, 2020)

BYOL works even without batch statistics. - Pierre H. Richemond; Jean-Bastien Grill; Florent Altché; Corentin Tallec; Florian Strub; Andrew Brock; Samuel L. Smith; Soham De; Razvan Pascanu; Bilal Piot; Michal Valko (CoRR, 2020)

Broaden Your Views for Self-Supervised Video Learning. - Adrià Recasens; Pauline Luc; Jean-Baptiste Alayrac; Luyu Wang; Florian Strub; Corentin Tallec; Mateusz Malinowski; Viorica Patraucean; Florent Altché; Michal Valko; Jean-Bastien Grill; Aäron van den Oord; et al. (ICCV, 2021)

Learning Successor States and Goal-Dependent Values: A Mathematical Viewpoint. - Léonard Blier; Corentin Tallec; Yann Ollivier (CoRR, 2021)

Bootstrapped Representation Learning on Graphs. - Shantanu Thakoor; Corentin Tallec; Mohammad Gheshlaghi Azar; Rémi Munos; Petar Velickovic; Michal Valko (CoRR, 2021)

Shaking the foundations: delusions in sequence models for interaction and control. - Pedro A. Ortega; Markus Kunesch; Grégoire Delétang; Tim Genewein; Jordi Grau-Moya; Joel Veness; Jonas Buchli; Jonas Degrave; Bilal Piot; Julien Pérolat; Tom Everitt; Corentin Tallec; et al. (CoRR, 2021)

Emergent Communication at Scale. - Rahma Chaabouni 001; Florian Strub; Florent Altché; Eugene Tarassov; Corentin Tallec; Elnaz Davoodi; Kory Wallace Mathewson; Olivier Tieleman; Angeliki Lazaridou; Bilal Piot (ICLR, 2022)

Large-Scale Representation Learning on Graphs via Bootstrapping. - Shantanu Thakoor; Corentin Tallec; Mohammad Gheshlaghi Azar; Mehdi Azabou; Eva L. Dyer; Rémi Munos; Petar Velickovic; Michal Valko (ICLR, 2022)

BYOL-Explore: Exploration by Bootstrapped Prediction. - Zhaohan Guo; Shantanu Thakoor; Miruna Pislar; Bernardo Ávila Pires; Florent Altché; Corentin Tallec; Alaa Saade; Daniele Calandriello; Jean-Bastien Grill; Yunhao Tang; Michal Valko; Rémi Munos; et al. (NeurIPS, 2022)

Emergent Communication: Generalization and Overfitting in Lewis Games. - Mathieu Rita; Corentin Tallec; Paul Michel; Jean-Bastien Grill; Olivier Pietquin; Emmanuel Dupoux; Florian Strub (NeurIPS, 2022)

Self-conditioned Embedding Diffusion for Text Generation. - Robin Strudel; Corentin Tallec; Florent Altché; Yilun Du; Yaroslav Ganin; Arthur Mensch; Will Grathwohl; Nikolay Savinov; Sander Dieleman; Laurent Sifre; Rémi Leblond (CoRR, 2022)

Curiosity in hindsight. - Daniel Jarrett; Corentin Tallec; Florent Altché; Thomas Mesnard; Rémi Munos; Michal Valko (CoRR, 2022)

Curiosity in Hindsight: Intrinsic Exploration in Stochastic Environments. - Daniel Jarrett; Corentin Tallec; Florent Altché; Thomas Mesnard; Rémi Munos; Michal Valko (ICML, 2023)