One unified API for world models that imagine, plan, and act — a PyTorch toolkit shipping DreamerV3, TD-MPC2, and more

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.