A modular PyTorch library designed for learning, training, and deploying world models across various environments.

Demo implementations of JEPA World Models to support research

Emergentia is a neural-symbolic discovery engine that extracts parsimonious physical laws from noisy particle trajectory data. It combines deep learning to model complex forces with symbolic regression to rediscover human-readable, mathematically interpretable equations of motion.

CARDIOKOOP - Control-aware Koopman deep learning framework for real-time hemodynamic forecasting and cardiovascular digital twin applications.