Using biconnected components for efficient identification of upstream features in large spatial networks (GIS cup). - Zach Goldthorpe; Jason Cannon; Jesse Farebrother; Zachary Friggstad; Mario A. Nascimento (SIGSPATIAL/GIS, 2018)

Generalization and Regularization in DQN. - Jesse Farebrother; Marlos C. Machado; Michael Bowling (CoRR, 2018)

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)

Investigating Multi-task Pretraining and Generalization in Reinforcement Learning. - Adrien Ali Taïga; Rishabh Agarwal; Jesse Farebrother; Aaron C. Courville; Marc G. Bellemare (ICLR, 2023)

Learning and Controlling Silicon Dopant Transitions in Graphene using Scanning Transmission Electron Microscopy. - Max Schwarzer; Jesse Farebrother; Joshua Greaves; Ekin Dogus Cubuk; Rishabh Agarwal; Aaron C. Courville; Marc G. Bellemare; Sergei V. Kalinin; Igor Mordatch; Pablo Samuel Castro; Kevin M. Roccapriore (CoRR, 2023)

Stop Regressing: Training Value Functions via Classification for Scalable Deep RL. - Jesse Farebrother; Jordi Orbay; Quan Vuong; Adrien Ali Taïga; Yevgen Chebotar; Ted Xiao; Alex Irpan; Sergey Levine; Pablo Samuel Castro; Aleksandra Faust; Aviral Kumar; Rishabh Agarwal (ICML, 2024)

Mixtures of Experts Unlock Parameter Scaling for Deep RL. - Johan S. Obando-Ceron; Ghada Sokar; Timon Willi; Clare Lyle; Jesse Farebrother; Jakob Nicolaus Foerster; Gintare Karolina Dziugaite; Doina Precup; Pablo Samuel Castro (ICML, 2024)

A Distributional Analogue to the Successor Representation. - Harley Wiltzer; Jesse Farebrother; Arthur Gretton; Yunhao Tang; André Barreto 001; Will Dabney; Marc G. Bellemare; Mark Rowland 001 (ICML, 2024)

CALE: Continuous Arcade Learning Environment. - Jesse Farebrother; Pablo Samuel Castro (NeurIPS, 2024)

Foundations of Multivariate Distributional Reinforcement Learning. - Harley Wiltzer; Jesse Farebrother; Arthur Gretton; Mark Rowland 001 (NeurIPS, 2024)

Non-Adversarial Inverse Reinforcement Learning via Successor Feature Matching. - Arnav Kumar Jain; Harley Wiltzer; Jesse Farebrother; Irina Rish; Glen Berseth; Sanjiban Choudhury (ICLR, 2025)

Zero-Shot Whole-Body Humanoid Control via Behavioral Foundation Models. - Andrea Tirinzoni; Ahmed Touati; Jesse Farebrother; Mateusz Guzek; Anssi Kanervisto; Yingchen Xu; Alessandro Lazaric; Matteo Pirotta (ICLR, 2025)

Temporal Difference Flows. - Jesse Farebrother; Matteo Pirotta; Andrea Tirinzoni; Rémi Munos; Alessandro Lazaric; Ahmed Touati (CoRR, 2025)