Continuous Hierarchical Representations with Poincaré Variational Auto-Encoders. - Emile Mathieu; Charline Le Lan; Chris J. Maddison; Ryota Tomioka; Yee Whye Teh (NeurIPS, 2019)

Hierarchical Representations with Poincaré Variational Auto-Encoders. - Emile Mathieu; Charline Le Lan; Chris J. Maddison; Ryota Tomioka; Yee Whye Teh (CoRR, 2019)

Metrics and Continuity in Reinforcement Learning. - Charline Le Lan; Marc G. Bellemare; Pablo Samuel Castro (AAAI, 2021)

LieTransformer: Equivariant Self-Attention for Lie Groups. - Michael J. Hutchinson; Charline Le Lan; Sheheryar Zaidi; Emilien Dupont; Yee Whye Teh; Hyunjik Kim (ICML, 2021)

Perfect Density Models Cannot Guarantee Anomaly Detection. - Charline Le Lan; Laurent Dinh (Entropy, 2021)

On the Generalization of Representations in Reinforcement Learning. - Charline Le Lan; Stephen Tu; Adam Oberman; Rishabh Agarwal; Marc G. Bellemare (AISTATS, 2022)

A Novel Stochastic Gradient Descent Algorithm for Learning Principal Subspaces. - Charline Le Lan; Joshua Greaves; Jesse Farebrother; Mark Rowland 001; Fabian Pedregosa; Rishabh Agarwal; Marc G. Bellemare (AISTATS, 2023)

Proto-Value Networks: Scaling Representation Learning with Auxiliary Tasks. - Jesse Farebrother; Joshua Greaves; Rishabh Agarwal; Charline Le Lan; Ross Goroshin; Pablo Samuel Castro; Marc G. Bellemare (ICLR, 2023)

Revisiting Bisimulation: A Sampling-Based State Similarity Pseudo-metric. - Charline Le Lan; Rishabh Agarwal (Tiny Papers @ ICLR, 2023)

Bootstrapped Representations in Reinforcement Learning. - Charline Le Lan; Stephen Tu; Mark Rowland 001; Anna Harutyunyan; Rishabh Agarwal; Marc G. Bellemare; Will Dabney (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)

Gemma: Open Models Based on Gemini Research and Technology. - Thomas Mesnard; Cassidy Hardin; Robert Dadashi; Surya Bhupatiraju; Shreya Pathak; Laurent Sifre; Morgane Rivière; Mihir Sanjay Kale; Juliette Love; Pouya Tafti; Léonard Hussenot; Aakanksha Chowdhery; et al. (CoRR, 2024)

Gemma 2: Improving Open Language Models at a Practical Size. - Morgane Rivière; Shreya Pathak; Pier Giuseppe Sessa; Cassidy Hardin; Surya Bhupatiraju; Léonard Hussenot; Thomas Mesnard; Bobak Shahriari; Alexandre Ramé; Johan Ferret; Peter Liu; Pouya Tafti; et al. (CoRR, 2024)

Gemma 3 Technical Report. - Aishwarya Kamath; Johan Ferret; Shreya Pathak; Nino Vieillard; Ramona Merhej; Sarah Perrin; Tatiana Matejovicova; Alexandre Ramé; Morgane Rivière; Louis Rouillard; Thomas Mesnard; Geoffrey Cideron; et al. (CoRR, 2025)