LM-PyTorch-Training

Learning in infinite dimension with neural operators.

A library for differentiable nonlinear optimization

[CVPR 2022 Oral, Best Student Paper] EPro-PnP: Generalized End-to-End Probabilistic Perspective-n-Points for Monocular Object Pose Estimation

Graph Neural PDEs

18.S096 - Applications of Scientific Machine Learning

PyDEns is a framework for solving Ordinary and Partial Differential Equations (ODEs & PDEs) using neural networks

An interactive book about the Riemann problem for hyperbolic PDEs, using Jupyter notebooks.

[NeurIPS 2021] Galerkin Transformer: a linear attention without softmax for Partial Differential Equations

Automatic Finite Difference PDE solving with Julia SciML

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