Jesse Farebrother

Publication Activity (10 Years)

Years Active: 2018-2024
Publications (10 Years): 11

Top Topics

Transmission Electron Microscopy

Reinforcement Learning

Stochastic Gradient Descent

Top Venues

Publications

Harley Wiltzer, Jesse Farebrother, Arthur Gretton, Yunhao Tang, André Barreto, Will Dabney, Marc G. Bellemare, Mark Rowland
A Distributional Analogue to the Successor Representation. CoRR (2024)
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
Stop Regressing: Training Value Functions via Classification for Scalable Deep RL. CoRR (2024)
Johan S. Obando-Ceron, Ghada Sokar, Timon Willi, Clare Lyle, Jesse Farebrother, Jakob N. Foerster, Gintare Karolina Dziugaite, Doina Precup, Pablo Samuel Castro
Mixtures of Experts Unlock Parameter Scaling for Deep RL. CoRR (2024)
Jesse Farebrother, Joshua Greaves, Rishabh Agarwal, Charline Le Lan, Ross Goroshin, Pablo Samuel Castro, Marc G. Bellemare
Proto-Value Networks: Scaling Representation Learning with Auxiliary Tasks. CoRR (2023)
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
Learning and Controlling Silicon Dopant Transitions in Graphene using Scanning Transmission Electron Microscopy. CoRR (2023)
Charline Le Lan, Joshua Greaves, Jesse Farebrother, Mark Rowland, Fabian Pedregosa, Rishabh Agarwal, Marc G. Bellemare
A Novel Stochastic Gradient Descent Algorithm for Learning Principal Subspaces. AISTATS (2023)
Adrien Ali Taïga, Rishabh Agarwal, Jesse Farebrother, Aaron C. Courville, Marc G. Bellemare
Investigating Multi-task Pretraining and Generalization in Reinforcement Learning. ICLR (2023)
Jesse Farebrother, Joshua Greaves, Rishabh Agarwal, Charline Le Lan, Ross Goroshin, Pablo Samuel Castro, Marc G. Bellemare
Proto-Value Networks: Scaling Representation Learning with Auxiliary Tasks. ICLR (2023)
Charline Le Lan, Joshua Greaves, Jesse Farebrother, Mark Rowland, Fabian Pedregosa, Rishabh Agarwal, Marc G. Bellemare
A Novel Stochastic Gradient Descent Algorithm for Learning Principal Subspaces. CoRR (2022)
Jesse Farebrother, Marlos C. Machado, Michael Bowling
Generalization and Regularization in DQN. CoRR (2018)
Zach Goldthorpe, Jason Cannon, Jesse Farebrother, Zachary Friggstad, Mario A. Nascimento
Using biconnected components for efficient identification of upstream features in large spatial networks (GIS cup). SIGSPATIAL/GIS (2018)