Representation-Learning

Discrete Codebook World Models for Continuous Control

Entropy Regularized Task Representation Learning for Offline Meta-Reinforcement Learning

iQRL: Implicitly Quantized Representations for Sample-Efficient Reinforcement Learning

I will be presenting our research on self-supervised representation learning for reinforcement learning at the [International Workshop of Intelligent Autonomous Learning Systems …

iQRL - Implicitly Quantized Representations for Sample-efficient Reinforcement Learning

Quantized Representations Prevent Dimensional Collapse in Self-predictive RL

Implicitly Quantized Representations for Reinforcement Learning

Learning representations for reinforcement learning (RL) has shown much promise for continuous control. In this project, we investigate using vector quantization to prevent …