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06/16/2023
Bootstrapped Representations in Reinforcement Learning
In reinforcement learning (RL), state representations are key to dealing...
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04/25/2023
Proto-Value Networks: Scaling Representation Learning with Auxiliary Tasks
Auxiliary tasks improve the representations learned by deep reinforcemen...
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12/08/2022
A Novel Stochastic Gradient Descent Algorithm for Learning Principal Subspaces
Many machine learning problems encode their data as a matrix with a poss...
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12/06/2022
Understanding Self-Predictive Learning for Reinforcement Learning
We study the learning dynamics of self-predictive learning for reinforce...
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03/01/2022
On the Generalization of Representations in Reinforcement Learning
In reinforcement learning, state representations are used to tractably d...
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02/02/2021
Metrics and continuity in reinforcement learning
In most practical applications of reinforcement learning, it is untenabl...
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12/20/2020
LieTransformer: Equivariant self-attention for Lie Groups
Group equivariant neural networks are used as building blocks of group i...
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12/07/2020
Perfect density models cannot guarantee anomaly detection
Thanks to the tractability of their likelihood, some deep generative mod...
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01/17/2019
