Dopamine: A Research Framework for Deep Reinforcement Learning. - Pablo Samuel Castro; Subhodeep Moitra; Carles Gelada; Saurabh Kumar 004; Marc G. Bellemare (CoRR, 2018)

Off-Policy Deep Reinforcement Learning by Bootstrapping the Covariate Shift. - Carles Gelada; Marc G. Bellemare (AAAI, 2019)

DeepMDP: Learning Continuous Latent Space Models for Representation Learning. - Carles Gelada; Saurabh Kumar 004; Jacob Buckman; Ofir Nachum; Marc G. Bellemare (ICML, 2019)

Hyperbolic Discounting and Learning over Multiple Horizons. - William Fedus; Carles Gelada; Yoshua Bengio; Marc G. Bellemare; Hugo Larochelle (CoRR, 2019)

Meta-Dataset: A Dataset of Datasets for Learning to Learn from Few Examples. - Eleni Triantafillou; Tyler Zhu; Vincent Dumoulin; Pascal Lamblin; Kelvin Xu; Ross Goroshin; Carles Gelada; Kevin Swersky; Pierre-Antoine Manzagol; Hugo Larochelle (CoRR, 2019)

Meta-Dataset: A Dataset of Datasets for Learning to Learn from Few Examples. - Eleni Triantafillou; Tyler Zhu; Vincent Dumoulin; Pascal Lamblin; Utku Evci; Kelvin Xu; Ross Goroshin; Carles Gelada; Kevin Swersky; Pierre-Antoine Manzagol; Hugo Larochelle (ICLR, 2020)

The Importance of Pessimism in Fixed-Dataset Policy Optimization. - Jacob Buckman; Carles Gelada; Marc G. Bellemare (ICLR, 2021)

Conformal Transformations for Symmetric Power Transformers. - Saurabh Kumar 004; Jacob Buckman; Carles Gelada; Sean Zhang (CoRR, 2025)

Scaling Context Requires Rethinking Attention. - Carles Gelada; Jacob Buckman; Sean Zhang; Txus Bach (CoRR, 2025)