Learning in infinite dimension with neural operators.

A library for scientific machine learning and physics-informed learning

Differentiable Fluid Dynamics Package

Tutorials on deep learning, Python, and dissipative particle dynamics

Welcome to the Physics-based Deep Learning Book (v0.2)

Computational Fluid Dynamics in JAX

PDEBench: An Extensive Benchmark for Scientific Machine Learning

Codebase for PINNacle: A Comprehensive Benchmark of Physics-Informed Neural Networks for Solving PDEs.

Using graph network to solve PDEs

Code for the paper "Poseidon: Efficient Foundation Models for PDEs"