Learning in infinite dimension with neural operators.

PDEBench: An Extensive Benchmark for Scientific Machine Learning

Physics-Informed Neural networks for Advanced modeling

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

Source code of "Learning nonlinear operators in latent spaces for real-time predictions of complex dynamics in physical systems."

Learning function operators with neural networks.

[ICLR24] A boundary-embedded neural operator that incorporates complex boundary shape and inhomogeneous boundary values

Rheology-informed Machine Learning Projects

Official implementation of Operator-ProbConserv: OOD UQ for Neural Operators

Implementation of Fourier Neural Operator from scratch

Bridging Neural Operators and Numerical Methods

Code for paper "FNOReg: Resolution-Robust Medical Image Registration Method Based on Fourier Neural Operator"