Jesse Farebrother

According to our database1, Jesse Farebrother authored at least 9 papers between 2018 and 2024.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

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Links

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Bibliography

2024
Stop Regressing: Training Value Functions via Classification for Scalable Deep RL.
CoRR, 2024

Mixtures of Experts Unlock Parameter Scaling for Deep RL.
CoRR, 2024

A Distributional Analogue to the Successor Representation.
CoRR, 2024

2023
Learning and Controlling Silicon Dopant Transitions in Graphene using Scanning Transmission Electron Microscopy.
CoRR, 2023

Investigating Multi-task Pretraining and Generalization in Reinforcement Learning.
Proceedings of the Eleventh International Conference on Learning Representations, 2023

Proto-Value Networks: Scaling Representation Learning with Auxiliary Tasks.
Proceedings of the Eleventh International Conference on Learning Representations, 2023

A Novel Stochastic Gradient Descent Algorithm for Learning Principal Subspaces.
Proceedings of the International Conference on Artificial Intelligence and Statistics, 2023

2018
Generalization and Regularization in DQN.
CoRR, 2018

Using biconnected components for efficient identification of upstream features in large spatial networks (GIS cup).
Proceedings of the 26th ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems, 2018


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