Jesse Farebrother

25 papers A* 10A 1Journal 13Unranked 1
YearRankTypeTitle / Venue / Authors
2026 J jnl
Compositional Planning with Jumpy World Models.
CoRR
Jesse Farebrother, Matteo Pirotta, Andrea Tirinzoni, Marc G. Bellemare, Alessandro Lazaric, Ahmed Touati
2025 A* conf
Non-Adversarial Inverse Reinforcement Learning via Successor Feature Matching.
ICLR
Arnav Kumar Jain, Harley Wiltzer, Jesse Farebrother, Irina Rish, Glen Berseth, Sanjiban Choudhury
2025 A* conf
Temporal Difference Flows.
ICML
Jesse Farebrother, Matteo Pirotta, Andrea Tirinzoni, Rémi Munos, Alessandro Lazaric, Ahmed Touati
2025 J jnl
Temporal Difference Flows.
CoRR
Jesse Farebrother, Matteo Pirotta, Andrea Tirinzoni, Rémi Munos, Alessandro Lazaric, Ahmed Touati
2025 A* conf
Zero-Shot Whole-Body Humanoid Control via Behavioral Foundation Models.
ICLR
Andrea Tirinzoni, Ahmed Touati, Jesse Farebrother, Mateusz Guzek, Anssi Kanervisto, Yingchen Xu, Alessandro Lazaric, Matteo Pirotta
2025 J jnl
Zero-Shot Whole-Body Humanoid Control via Behavioral Foundation Models.
CoRR
Andrea Tirinzoni, Ahmed Touati, Jesse Farebrother, Mateusz Guzek, Anssi Kanervisto, Yingchen Xu, Alessandro Lazaric, Matteo Pirotta
2024 A* conf
A Distributional Analogue to the Successor Representation.
ICML
Harley Wiltzer, Jesse Farebrother, Arthur Gretton, Yunhao Tang, André Barreto, Will Dabney, Marc G. Bellemare, Mark Rowland
2024 J jnl
A Distributional Analogue to the Successor Representation.
CoRR
Harley Wiltzer, Jesse Farebrother, Arthur Gretton, Yunhao Tang, André Barreto, Will Dabney, Marc G. Bellemare, Mark Rowland
2024 A* conf
CALE: Continuous Arcade Learning Environment.
NeurIPS
Jesse Farebrother, Pablo Samuel Castro
2024 J jnl
CALE: Continuous Arcade Learning Environment.
CoRR
Jesse Farebrother, Pablo Samuel Castro
2024 A* conf
Foundations of Multivariate Distributional Reinforcement Learning.
NeurIPS
Harley Wiltzer, Jesse Farebrother, Arthur Gretton, Mark Rowland
2024 J jnl
Foundations of Multivariate Distributional Reinforcement Learning.
CoRR
Harley Wiltzer, Jesse Farebrother, Arthur Gretton, Mark Rowland
2024 A* conf
Mixtures of Experts Unlock Parameter Scaling for Deep RL.
ICML
Johan S. Obando-Ceron, Ghada Sokar, Timon Willi, Clare Lyle, Jesse Farebrother, Jakob Nicolaus Foerster, Gintare Karolina Dziugaite, Doina Precup, Pablo Samuel Castro
2024 J jnl
Mixtures of Experts Unlock Parameter Scaling for Deep RL.
CoRR
Johan S. Obando-Ceron, Ghada Sokar, Timon Willi, Clare Lyle, Jesse Farebrother, Jakob N. Foerster, Gintare Karolina Dziugaite, Doina Precup, Pablo Samuel Castro
2024 J jnl
Non-Adversarial Inverse Reinforcement Learning via Successor Feature Matching.
CoRR
Arnav Kumar Jain, Harley Wiltzer, Jesse Farebrother, Irina Rish, Glen Berseth, Sanjiban Choudhury
2024 A* conf
Stop Regressing: Training Value Functions via Classification for Scalable Deep RL.
ICML
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
2024 J jnl
Stop Regressing: Training Value Functions via Classification for Scalable Deep RL.
CoRR
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
2023 A conf
A Novel Stochastic Gradient Descent Algorithm for Learning Principal Subspaces.
AISTATS
Charline Le Lan, Joshua Greaves, Jesse Farebrother, Mark Rowland, Fabian Pedregosa, Rishabh Agarwal, Marc G. Bellemare
2023 A* conf
Investigating Multi-task Pretraining and Generalization in Reinforcement Learning.
ICLR
Adrien Ali Taïga, Rishabh Agarwal, Jesse Farebrother, Aaron C. Courville, Marc G. Bellemare
2023 J jnl
Learning and Controlling Silicon Dopant Transitions in Graphene using Scanning Transmission Electron Microscopy.
CoRR
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
2023 A* conf
Proto-Value Networks: Scaling Representation Learning with Auxiliary Tasks.
ICLR
Jesse Farebrother, Joshua Greaves, Rishabh Agarwal, Charline Le Lan, Ross Goroshin, Pablo Samuel Castro, Marc G. Bellemare
2023 J jnl
Proto-Value Networks: Scaling Representation Learning with Auxiliary Tasks.
CoRR
Jesse Farebrother, Joshua Greaves, Rishabh Agarwal, Charline Le Lan, Ross Goroshin, Pablo Samuel Castro, Marc G. Bellemare
2022 J jnl
A Novel Stochastic Gradient Descent Algorithm for Learning Principal Subspaces.
CoRR
Charline Le Lan, Joshua Greaves, Jesse Farebrother, Mark Rowland, Fabian Pedregosa, Rishabh Agarwal, Marc G. Bellemare
2018 J jnl
Generalization and Regularization in DQN.
CoRR
Jesse Farebrother, Marlos C. Machado, Michael Bowling
2018 — conf
Using biconnected components for efficient identification of upstream features in large spatial networks (GIS cup).
SIGSPATIAL/GIS
Zach Goldthorpe, Jason Cannon, Jesse Farebrother, Zachary Friggstad, Mario A. Nascimento