← Search

Diana L Borsa

5 accepted papers

2025

A Unifying Framework for Action-Conditional Self-Predictive Reinforcement Learning

AISTATS 2025poster

Learning a good representation is a crucial challenge for reinforcement learning (RL) agents. Self-predictive algorithms jointly learn a latent representation and dynamics model by bootstrapping from future latent representations (BYOL). Recent work has developed theoretical insights into these algo…

Cited by 0SourceScholar
2025

Wasserstein Policy Optimization

ICML 2025poster

We introduce Wasserstein Policy Optimization (WPO), an actor-critic algorithm for reinforcement learning in continuous action spaces. WPO can be derived as an approximation to Wasserstein gradient flow over the space of all policies projected into a finite-dimensional parameter space (e.g., the weig…

Cited by 0SourcePDFScholar
2023

A State Representation for Diminishing Rewards

NeurIPS 2023poster

A common setting in multitask reinforcement learning (RL) demands that an agent rapidly adapt to various stationary reward functions randomly sampled from a fixed distribution. In such situations, the successor representation (SR) is a popular framework which supports rapid policy evaluation by deco…

Cited by 1SourcePDFScholar
2023

Representations and Exploration for Deep Reinforcement Learning using Singular Value Decomposition

ICML 2023poster

Representation learning and exploration are among the key challenges for any deep reinforcement learning agent. In this work, we provide a singular value decomposition based method that can be used to obtain representations that preserve the underlying transition structure in the domain. Perhaps int…

Cited by 5SourcePDFScholar