world-models

What problem does it solve?

This Skill provides a comprehensive guide to world models and Joint Embedding Predictive Architectures (JEPA), addressing the challenges of self-supervised learning and reinforcement learning agents.

Core Features & Use Cases

• Understanding JEPA: Offers in-depth explanations of JEPA, including its architecture, loss functions, and variants.
• World Models: Delves into various world models like Dreamer, MuZero, TD-MPC, DIAMOND, and Genie, explaining their architectures and use cases.
• Use Case: A researcher looking to implement a world model for robot planning can use this Skill to understand the nuances of different models and choose the most suitable one.

Quick Start

To learn about I-JEPA, use the world-models skill to read the 'I-JEPA — Self-Supervised Learning from Images with a Joint-Embedding Predictive Architecture' paper.