ncsa / GeomDeepONet
A novel DeepONet architecture that is specifically designed for generating predictions on different 3D geometries discretized by different number of mesh nodes.
☆12Updated 8 months ago
Alternatives and similar repositories for GeomDeepONet:
Users that are interested in GeomDeepONet are comparing it to the libraries listed below
- Prediction of Fluid Flow in Porous Media by Sparse Observations and Physics-Informed PointNet☆11Updated 7 months ago
- Implementation of a ResUNet-based DeepONet for predicting stress distribution on variable input geometries subject to variable loads. A R…☆12Updated last year
- A sequential DeepONet model implementation that uses a recurrent neural network (GRU and LSTM) in the branch and a feed-forward neural ne…☆13Updated 10 months ago
- Reduced-Order Modeling of Fluid Flows with Transformers☆23Updated last year
- ☆28Updated 2 years ago
- This repository contains code, which was used to generate large-scale results in the HINTS paper.☆27Updated 5 months ago
- ☆10Updated last year
- DeepONet extrapolation☆26Updated last year
- PyTorch implemention of the Position-induced Transformer for operator learning in partial differential equations☆17Updated 4 months ago
- Code for Mesh Transformer describes in the EAGLE dataset☆38Updated last month
- Physics-informed graph neural Galerkin networks: A unified framework for solving PDE-governed forward and inverse problems☆49Updated 3 years ago
- In this repository, you will find the different python scripts to train the available models on the AirfRANS dataset proposed at the Neur…☆47Updated 2 months ago
- ☆23Updated 8 months ago
- ☆14Updated 7 months ago
- Multifidelity DeepONet☆30Updated last year
- Physics-informed radial basis network☆30Updated 10 months ago
- Discontinuity Computing Using Physics-Informed Neural Network☆23Updated 11 months ago
- ☆15Updated 7 months ago
- Code for 'Physics-Informed Neural Networks for Shell Structures'☆35Updated 7 months ago
- Source code of "Learning nonlinear operators in latent spaces for real-time predictions of complex dynamics in physical systems."☆58Updated 8 months ago
- Multi-fidelity reduced-order surrogate modeling☆19Updated 3 months ago
- Code accompanying "Inverse-Dirichlet Weighting Enables Reliable Training of Physics Informed Neural Networks", Maddu et al., 2021☆10Updated 3 years ago
- GCA-ROM is a library which implements graph convolutional autoencoder architecture as a nonlinear model order reduction strategy.☆33Updated 8 months ago
- Code for "Robust flow field reconstruction from limited measurements vis sparse representation" (J. Callaham, K. Maeda, and S. Brunton 20…☆14Updated 6 years ago
- Learning two-phase microstructure evolution using neural operators and autoencoder architectures☆23Updated 11 months ago
- XPINN code written in TensorFlow 2☆27Updated 2 years ago
- Coupled-Automatic-Numerical differentiation scheme for physics-informed neural network (can-PINN)☆25Updated last year
- Physics-informed neural networks for identifying material properties in solid mechanics☆17Updated last year
- ☆21Updated 2 weeks ago
- ☆26Updated 2 years ago