Positron's Milky Way Energy Loss using Operator learning
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Updated
Mar 19, 2024
Positron's Milky Way Energy Loss using Operator learning
Using FNO to learning elasticity model of composite materials
Submission to the Stanford FLAME AI 2023 - ML Challenge
Use DeepONet to solve Hamilton equations
Code for the paper ``Error Bounds for Learning with Vector-Valued Random Features''
Code for the paper "The Random Feature Model for Input-Output Maps between Banach Spaces"
Code for ICML 24 paper "Implicit Representations via Operator Learning"
The first global dataset for physics-ML seismic wavefield modeling and full-waveform inversion
Implementation of neural operator papers in PyTorch for easier usage. Achieve SOTA in PDE prediction.
Neural Operators with Applications to the Helmholtz Equation
Neural Operator-Assisted Computational Fluid Dynamics in PyTorch
This repository contains the code for the paper: Deciphering and integrating invariants for neural operator learning with various physical mechanisms, National Science Review, 2024
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
An extension of Fourier Neural Operator to finite-dimensional input and/or output spaces.
A multiphase multiphysics dataset and benchmarks for scientific machine learning
Codomain attention neural operator for single to multi-physics PDE adaptation.
Derivative-Informed Neural Operator: An Efficient Framework for High-Dimensional Parametric Derivative Learning
Official implementation of Scalable Transformer for PDE surrogate modelling
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