jtoleary / SPINNLinks
Stochastic Physics-Informed Neural Networks: A Moment-Matching Framework for Learning Hidden Physics within Stochastic Differential Equations
☆14Updated 3 years ago
Alternatives and similar repositories for SPINN
Users that are interested in SPINN are comparing it to the libraries listed below
Sorting:
- ☆45Updated 2 years ago
- Code for Mesh Transformer describes in the EAGLE dataset☆42Updated 8 months ago
- Simple demo on implementing data driven and physics informed Deep O Nets in pytorch☆19Updated last year
- Official repo for separable operator networks -- extreme-scale operator learning for parametric PDEs.☆32Updated last year
- ☆14Updated 4 years ago
- This repository contains the code and models for our paper "Investigating and Mitigating Failure Modes in Physics-informed Neural Network…☆19Updated last year
- Discontinuity Computing Using Physics-Informed Neural Network☆26Updated last year
- This repository contains code, which was used to generate large-scale results in the HINTS paper.☆33Updated last year
- ☆16Updated last year
- This codes calculates the dimensionalized POD and uses SINDy from the PySINDy python package to build a data-driven model for it. The cod…☆21Updated 4 years ago
- ☆46Updated 7 months ago
- Official implementation of Scalable Transformer for PDE surrogate modelling☆52Updated last year
- Reliable extrapolation of deep neural operators informed by physics or sparse observations☆27Updated 2 years ago
- ☆28Updated last year
- library for querying the Johns Hopkins Turbulence Database (JHTDB)☆15Updated this week
- Fourier Neural Operators to solve for Allen Cahn PDE equations☆18Updated 3 years ago
- This is the repository for the code used in the ICML23 paper called "Achieving High Accuracy with PINNs via Energy Natural Gradient Desce…☆22Updated last year
- Transformed Generative Pre-Trained Physics-Informed Neural Networks (TGPT-PINN), a framework that extends Physics-Informed Neural Network…☆17Updated last year
- ☆12Updated this week
- GCA-ROM is a library which implements graph convolutional autoencoder architecture as a nonlinear model order reduction strategy.☆36Updated last month
- ☆55Updated 3 years ago
- Separabale Physics-Informed DeepONets in JAX☆14Updated 11 months ago
- XPINN code written in TensorFlow 2☆28Updated 2 years ago
- ☆10Updated 2 years ago
- Generative Learning for Forecasting the Dynamics of High Dimensional Complex Systems☆37Updated 7 months ago
- In this repository, you will find the different python scripts to train the available models on the AirfRANS dataset proposed at the Neur…☆56Updated 9 months ago
- Neural Galerkin☆16Updated 2 years ago
- ☆12Updated last year
- Official Code for ICML 2024 paper "TENG: Time-Evolving Natural Gradient for Solving PDEs With Deep Neural Nets Toward Machine Precision"☆12Updated 11 months ago
- DON-LSTM: Multi-Resolution Learning with DeepONets and Long-Short Term Memory Neural Networks☆11Updated last month