geelenr / quad_manifoldLinks
Supporting codes for the numerical implementations in the paper "Operator inference for non-intrusive model reduction with quadratic manifolds" by Rudy Geelen, Stephen Wright and Karen Willcox
☆11Updated 3 years ago
Alternatives and similar repositories for quad_manifold
Users that are interested in quad_manifold are comparing it to the libraries listed below
Sorting:
- A sequential DeepONet model implementation that uses a recurrent neural network (GRU and LSTM) in the branch and a feed-forward neural ne…☆18Updated last year
- This repository comprises Jupyter Notebooks that serve as supplementary material to the journal article titled "Review of Multifidelity M…☆12Updated 2 years ago
- Multi-fidelity reduced-order surrogate modeling☆29Updated 6 months ago
- Surrogate Modeling for Fluid Flows Based on Physics-Constrained Label-Free Deep Learning☆93Updated 2 years ago
- A Python package for spectral proper orthogonal decomposition (SPOD).☆115Updated 3 weeks ago
- POD-PINN code and manuscript☆57Updated last year
- POD and DMD decomposition of data from fluid dynamics. This work has been produced during my internship at the von Karman Institute for F…☆34Updated 5 years ago
- PhyGeoNet: Physics-Informed Geometry-Adaptive Convolutional Neural Networks for Solving Parametric PDEs on Irregular Domain☆91Updated 4 years ago
- Multifidelity deep neural operators for efficient learning of partial differential equations with application to fast inverse design of n…☆38Updated 2 years ago
- PINNs for 2D Incompressible Navier-Stokes Equation☆57Updated last year
- KTH-FlowAI / beta-Variational-autoencoders-and-transformers-for-reduced-order-modelling-of-fluid-flows☆41Updated 8 months ago
- Source code of 'Deep transfer operator learning for partial differential equations under conditional shift'.☆75Updated 2 years ago
- GCA-ROM is a library which implements graph convolutional autoencoder architecture as a nonlinear model order reduction strategy.☆36Updated last month
- Reduced-Order Modeling of Fluid Flows with Transformers☆24Updated 2 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…☆57Updated last year
- This repository contains the files used in the paper " Reduced-order Model for Fluid Flows via Neural Ordinary Differential Equations"☆19Updated 2 years ago
- ☆54Updated 3 years ago
- Enhancing Dynamic Mode Decomposition using Autoencoder Networks.☆35Updated 4 years ago
- We propose a conservative physics-informed neural network (cPINN) on decompose domains for nonlinear conservation laws. The conservation …☆76Updated 2 years ago
- Operator Inference for data-driven, non-intrusive model reduction of dynamical systems.☆77Updated 2 months ago
- hp-VPINNs: variational physics-informed neural network with domain decomposition is a general framework to solve differential equations☆87Updated 4 months ago
- Physics-constrained auto-regressive convolutional neural networks for dynamical PDEs☆93Updated 3 years ago
- PDE Preserved Neural Network☆59Updated 7 months ago
- Competitive Physics Informed Networks☆32Updated last year
- ☆91Updated last year
- Sparse Physics-based and Interpretable Neural Networks☆52Updated 4 years ago
- parallel PINNs; RANS equations; spatiotemporal parallel; PINNs☆33Updated last year
- Physics-informed graph neural Galerkin networks: A unified framework for solving PDE-governed forward and inverse problems☆59Updated 3 years ago
- A collection of Jupyter notebooks providing tutorials on reduced order modeling techniques like DeepONet, FNO, DL-ROM, and POD-DL-ROM. Ea…☆28Updated 11 months ago
- Easy Reduced Basis method☆92Updated last week