TD-JEPA: Latent-predictive Representations for Zero-Shot Reinforcement Learning

ICLROral2026

Authors
Marco Bagatella, Matteo Pirotta, Ahmed Touati, Alessandro Lazaric, Andrea Tirinzoni
Affiliation
Max Planck Institute for Intelligent Systems, Max Planck Institute for Intelligent Systems
Venue
ICLR 2026
Track
Oral

TL;DR

We propose a temporal-difference latent-predictive method for zero-shot unsupervised RL.

Opening excerpt from the authors’ abstract. source

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Topics

reinforcement learning zero-shot

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