Implementation of neural operator papers in PyTorch for easier usage. Achieve SOTA in PDE prediction.
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Updated
Jul 11, 2022 - Python
Implementation of neural operator papers in PyTorch for easier usage. Achieve SOTA in PDE prediction.
Datasets and code for results presented in the BOON paper
Using FNO to learning elasticity model of composite materials
Official implementation of the NeurIPS 23 spotlight paper of ♾️InfGCN♾️.
This repository contains the code for the paper: Monte Carlo Neural PDE Solver for Learning PDEs via Probabilistic Representation
Derivative-Informed Neural Operator: An Efficient Framework for High-Dimensional Parametric Derivative Learning
Automatic Functional Differentiation in JAX
Code for the paper "The Random Feature Model for Input-Output Maps between Banach Spaces"
This repository contains the code for the paper: Deciphering and integrating invariants for neural operator learning with various physical mechanisms, National Science Review, 2024
Positron's Milky Way Energy Loss using Operator learning
Official implementation of Scalable Transformer for PDE surrogate modelling
No need to train, he's a smooth operator
A multiphase multiphysics dataset and benchmarks for scientific machine learning
Code for the paper ``Error Bounds for Learning with Vector-Valued Random Features''
Use DeepONet to solve Hamilton equations
Codomain attention neural operator for single to multi-physics PDE adaptation.
Submission to the Stanford FLAME AI 2023 - ML Challenge
Neural Operators with Applications to the Helmholtz Equation
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