Learning in infinite dimension with neural operators.

A library for Koopman Neural Operator with Pytorch.

[NeurIPS 2021] Galerkin Transformer: Neural Operator built on Attention for PDEs

This repository is the official implementation of the paper Convolutional Neural Operators for robust and accurate learning of PDEs

[ICLR26 Oral] RealPDEBench: A Benchmark for Complex Physical Systems with Paired Real-World and Simulated Data

Automatic Functional Differentiation in JAX

[ICLR 2025] Neural Operator-Assisted Computational Fluid Dynamics in PyTorch

Codomain attention neural operator for single to multi-physics PDE adaptation.

ICML2024: Equivariant Graph Neural Operator for Modeling 3D Dynamics

[ICLR 2025] Wavelet Diffusion Neural Operator (WDNO) uses diffusion models on wavelet space for generative PDE simulation and control.

Efficient, Accurate, and Streamlined Training of Physics-Informed Neural Networks

Official implementation of Scalable Transformer for PDE surrogate modelling

A multiphase multiphysics dataset and benchmarks for scientific machine learning

Datasets and code for results presented in the BOON paper

No need to train, he's a smooth operator

A curated list of 113 AI-ready tools for Computer-Aided Engineering — CFD, FEA, SPH, DEM, differentiable simulation, neural operators, PINNs, MCP servers. Python APIs, CLI, mesh generation, optimization.

The first global synthetic dataset for physics-ML seismic wavefield modeling and full-waveform inversion

This repository contains the code for the paper: Monte Carlo Neural PDE Solver for Learning PDEs via Probabilistic Representation (IEEE TPAMI 2025)

[TMLR 2026] GIOROM, sampling based model-order reduction for Lagrangian systems