JEPA-x: Cross-Predictive Physics Grounding for Forecastable Latent Dynamics
cs.LG
Submitted: 2026-08-25
Updated: 2026-08-28
Terminology
Sources
- LeJEPA: Provable and Scalable Self-Supervised Learning Without the Heuristics
- MC-JEPA: A Joint-Embedding Predictive Architecture for Self-Supervised Learning of Motion and Content Features
- Revisiting Feature Prediction for Learning Visual Representations from Video
- PIGDreamer: Privileged Information Guided World Models for Safe Partially Observable Reinforcement Learning
- Pri4R: Learning World Dynamics for Vision-Language-Action Models with Privileged 4D Representation
- LeWorldModel: Stable End-to-End Joint-Embedding Predictive Architecture from Pixels
- Phys-JEPA: Physics-Informed Latent World Models for Multivariate Time-Series Forecasting
- DeepMind Control Suite
- PhyLatent: Learning Dynamics-Relevant Representations for JEPA World Models
- DINO-WM: World Models on Pre-trained Visual Features enable Zero-shot Planning
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