Efficiently applying attention to sequential data with the Recurrent Discounted Attention unit. - Brendan Maginnis; Pierre H. Richemond (CoRR, 2017)

On Wasserstein Reinforcement Learning and the Fokker-Planck equation. - Pierre H. Richemond; Brendan Maginnis (CoRR, 2017)

A short variational proof of equivalence between policy gradients and soft Q learning. - Pierre H. Richemond; Brendan Maginnis (CoRR, 2017)

Combining learning rate decay and weight decay with complexity gradient descent - Part I. - Pierre H. Richemond; Yike Guo (CoRR, 2019)

Static Activation Function Normalization. - Pierre H. Richemond; Yike Guo (CoRR, 2019)

Biologically inspired architectures for sample-efficient deep reinforcement learning. - Pierre H. Richemond; Arinbjörn Kolbeinsson; Yike Guo (CoRR, 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)

Zipfian Environments for Reinforcement Learning. - Stephanie C. Y. Chan; Andrew Kyle Lampinen; Pierre Harvey Richemond; Felix Hill (CoLLAs, 2022)

Data Distributional Properties Drive Emergent In-Context Learning in Transformers. - Stephanie C. Y. Chan; Adam Santoro; Andrew K. Lampinen; Jane X. Wang; Aaditya K. Singh; Pierre H. Richemond; James L. McClelland; Felix Hill (NeurIPS, 2022)

Categorical SDEs with Simplex Diffusion. - Pierre H. Richemond; Sander Dieleman; Arnaud Doucet (CoRR, 2022)

Continuous diffusion for categorical data. - Sander Dieleman; Laurent Sartran; Arman Roshannai; Nikolay Savinov; Yaroslav Ganin; Pierre H. Richemond; Arnaud Doucet; Robin Strudel; Chris Dyer; Conor Durkan; Curtis Hawthorne; Rémi Leblond; et al. (CoRR, 2022)

SemPPL: Predicting Pseudo-Labels for Better Contrastive Representations. - Matko Bosnjak; Pierre Harvey Richemond; Nenad Tomasev; Florian Strub; Jacob C. Walker; Felix Hill; Lars Holger Buesing; Razvan Pascanu; Charles Blundell; Jovana Mitrovic (ICLR, 2023)

The Edge of Orthogonality: A Simple View of What Makes BYOL Tick. - Pierre Harvey Richemond; Allison C. Tam; Yunhao Tang; Florian Strub; Bilal Piot; Felix Hill (ICML, 2023)

Understanding Self-Predictive Learning for Reinforcement Learning. - Yunhao Tang; Zhaohan Daniel Guo; Pierre Harvey Richemond; Bernardo Ávila Pires; Yash Chandak; Rémi Munos; Mark Rowland 001; Mohammad Gheshlaghi Azar; Charline Le Lan; Clare Lyle; András György 001; Shantanu Thakoor; et al. (ICML, 2023)

Human Alignment of Large Language Models through Online Preference Optimisation. - Daniele Calandriello; Zhaohan Daniel Guo; Rémi Munos; Mark Rowland 001; Yunhao Tang; Bernardo Ávila Pires; Pierre Harvey Richemond; Charline Le Lan; Michal Valko; Tianqi Liu 002; Rishabh Joshi; Zeyu Zheng; et al. (ICML, 2024)

Generalized Preference Optimization: A Unified Approach to Offline Alignment. - Yunhao Tang; Zhaohan Daniel Guo; Zeyu Zheng; Daniele Calandriello; Rémi Munos; Mark Rowland 001; Pierre Harvey Richemond; Michal Valko; Bernardo Ávila Pires; Bilal Piot (ICML, 2024)

Scaling Instructable Agents Across Many Simulated Worlds. - SIMA Team; Maria Abi Raad; Arun Ahuja; Catarina Barros; Frederic Besse; Andrew Bolt; Adrian Bolton; Bethanie Brownfield; Gavin Buttimore; Max Cant; Sarah Chakera; Stephanie C. Y. Chan; et al. (CoRR, 2024)

Offline Regularised Reinforcement Learning for Large Language Models Alignment. - Pierre Harvey Richemond; Yunhao Tang; Daniel Guo 001; Daniele Calandriello; Mohammad Gheshlaghi Azar; Rafael Rafailov; Bernardo Ávila Pires; Eugene Tarassov; Lucas Spangher; Will Ellsworth; Aliaksei Severyn; Jonathan Mallinson; et al. (CoRR, 2024)

ShiQ: Bringing back Bellman to LLMs. - Pierre Clavier; Nathan Grinsztajn; Raphaël Avalos; Yannis Flet-Berliac; Irem Ergün; Omar Darwiche Domingues; Eugene Tarassov; Olivier Pietquin; Pierre H. Richemond; Florian Strub; Matthieu Geist (CoRR, 2025)