NVIDIA/physicsnemo

A library for scientific machine learning and physics-informed learning

A differentiable PDE solving framework for machine learning

Physics Informed Deep Learning: Data-driven Solutions and Discovery of Nonlinear Partial Differential Equations

Learning in infinite dimension with neural operators.

Pretrain, finetune ANY AI model of ANY size on 1 or 10,000+ GPUs with zero code changes.

A coding-free framework built on PyTorch for reproducible deep learning studies. PyTorch Ecosystem. 🏆26 knowledge distillation methods presented at TPAMI, CVPR, ICLR, ECCV, NeurIPS, ICCV, AAAI, etc are implemented so far. 🎁 Trained models, training logs and configurations are available for ensuring the reproducibiliy and benchmark.

NVIDIA Cosmos is an open platform of world models, datasets, and tools that enables developers to build Physical AI for robots, autonomous vehicles, smart infrastructure, and more.

You like pytorch? You like micrograd? You love tinygrad! ❤️

Pytorch-based framework for solving parametric constrained optimization problems, physics-informed system identification, and parametric model predictive control.