fpichi / gca-romLinks
GCA-ROM is a library which implements graph convolutional autoencoder architecture as a nonlinear model order reduction strategy.
☆35Updated 3 weeks ago
Alternatives and similar repositories for gca-rom
Users that are interested in gca-rom are comparing it to the libraries listed below
Sorting:
- Multifidelity DeepONet☆34Updated 2 years ago
- ☆54Updated 2 years ago
- A sequential DeepONet model implementation that uses a recurrent neural network (GRU and LSTM) in the branch and a feed-forward neural ne…☆15Updated last year
- POD-PINN code and manuscript☆52Updated 8 months ago
- MIONet: Learning multiple-input operators via tensor product☆34Updated 2 years ago
- Source code for POD-DL-ROM: enhancing deep learning-based reduced order models for nonlinear parametrized PDEs by proper orthogonal decom…☆32Updated last year
- Reduced-Order Modeling of Fluid Flows with Transformers☆24Updated 2 years ago
- Discontinuity Computing Using Physics-Informed Neural Network☆24Updated last year
- Source code of 'Deep transfer operator learning for partial differential equations under conditional shift'.☆70Updated last year
- DeepONet extrapolation☆27Updated 2 years ago
- PDE Preserved Neural Network☆53Updated 2 months ago
- Sparse Physics-based and Interpretable Neural Networks☆50Updated 3 years ago
- Python codes for Locally Adaptive Activation Function (LAAF) used in deep neural networks. Please cite this work as "A D Jagtap, K Kawa…☆40Updated 2 years ago
- Multi-fidelity reduced-order surrogate modeling☆24Updated last month
- In this repository, you will find the different python scripts to train the available models on the AirfRANS dataset proposed at the Neur…☆55Updated 6 months ago
- A collection of Jupyter notebooks providing tutorials on reduced order modeling techniques like DeepONet, FNO, DL-ROM, and POD-DL-ROM. Ea…☆25Updated 5 months ago
- ☆26Updated last year
- Stiff-PINN: Physics-Informed Neural Network for Stiff Chemical Kinetics☆63Updated 3 years ago
- PhyGeoNet: Physics-Informed Geometry-Adaptive Convolutional Neural Networks for Solving Parametric PDEs on Irregular Domain☆86Updated 4 years ago
- We propose a conservative physics-informed neural network (cPINN) on decompose domains for nonlinear conservation laws. The conservation …☆71Updated 2 years ago
- Physics-informed graph neural Galerkin networks: A unified framework for solving PDE-governed forward and inverse problems☆55Updated 3 years ago
- XPINN code written in TensorFlow 2☆28Updated 2 years ago
- Surrogate Modeling for Fluid Flows Based on Physics-Constrained Label-Free Deep Learning☆88Updated last year
- Competitive Physics Informed Networks☆30Updated 9 months ago
- Coupled-Automatic-Numerical differentiation scheme for physics-informed neural network (can-PINN)☆29Updated last year
- ☆11Updated last week
- A library for dimensionality reduction on spatial-temporal PDE☆66Updated last year
- Official implementation of "PhyGNNet: Solving spatiotemporal PDEs with Physics-informed Graph Neural Network"☆47Updated 2 years ago
- ☆111Updated 5 months ago
- Source code of "Learning nonlinear operators in latent spaces for real-time predictions of complex dynamics in physical systems."☆63Updated 2 months ago