ContiPaolo / MultiFidelity_PODLinks
Multi-fidelity reduced-order surrogate modeling
☆28Updated 6 months ago
Alternatives and similar repositories for MultiFidelity_POD
Users that are interested in MultiFidelity_POD are comparing it to the libraries listed below
Sorting:
- This repository comprises Jupyter Notebooks that serve as supplementary material to the journal article titled "Review of Multifidelity M…☆12Updated 2 years ago
- Multifidelity deep neural operators for efficient learning of partial differential equations with application to fast inverse design of n…☆37Updated 2 years ago
- Proper Orthogonal Decomposition - Radial Basis Function (POD-RBF) Network☆69Updated last week
- ☆44Updated 3 years ago
- Source code for POD-DL-ROM: enhancing deep learning-based reduced order models for nonlinear parametrized PDEs by proper orthogonal decom…☆34Updated 2 years ago
- Reduced-Order Modeling of Fluid Flows with Transformers☆24Updated 2 years ago
- POD-PINN code and manuscript☆57Updated last year
- ☆40Updated 2 years ago
- This repository contains the files used in the paper " Reduced-order Model for Fluid Flows via Neural Ordinary Differential Equations"☆19Updated 2 years ago
- A collection of Jupyter notebooks providing tutorials on reduced order modeling techniques like DeepONet, FNO, DL-ROM, and POD-DL-ROM. Ea…☆27Updated 11 months ago
- parallel PINNs; RANS equations; spatiotemporal parallel; PINNs☆33Updated last year
- Physics-Constrained Bayesian Neural Network for Fluid Flow Reconstruction with Sparse and Noisy Data☆50Updated 5 years ago
- Discontinuity Computing Using Physics-Informed Neural Network☆26Updated last year
- Sparse Physics-based and Interpretable Neural Networks☆52Updated 4 years ago
- Physics-informed graph neural Galerkin networks: A unified framework for solving PDE-governed forward and inverse problems☆57Updated 3 years ago
- POD and DMD decomposition of data from fluid dynamics. This work has been produced during my internship at the von Karman Institute for F…☆33Updated 5 years ago
- GCA-ROM is a library which implements graph convolutional autoencoder architecture as a nonlinear model order reduction strategy.☆36Updated last month
- XPINN code written in TensorFlow 2☆28Updated 2 years ago
- Surrogate Modeling for Fluid Flows Based on Physics-Constrained Label-Free Deep Learning☆93Updated 2 years ago
- This repository contains the simple source codes of "Machine-learning-based reduced-order modeling for unsteady flows around bluff bodies…☆16Updated 4 years ago
- Physics-informed neural networks for highly compressible flows 🧠🌊☆28Updated 2 years ago
- PINN Implementation for IJCAI paper, "Physics-Informed Neural Networks: Minimizing Residual Loss with Wide Networks and Effective Activat…☆20Updated last year
- Frame-independent vector-cloud neural network for nonlocal constitutive modelling on arbitrary grids.☆11Updated 4 years ago
- Deep Learning for Reduced Order Modelling☆102Updated 4 years ago
- A Backward Compatible -- Physics Informed Neural Network for Allen Cahn and Cahn Hilliard Equations☆36Updated 3 years ago
- ☆88Updated last year
- ☆20Updated last year
- Sample codes of CNN-SINDy based reduced-order modeling for fluid flows by Fukami et al., JFM 2021.☆27Updated 4 years ago
- ☆12Updated 3 weeks ago
- Physics-guided neural network framework for elastic plates☆48Updated 3 years ago