stefaniafresca / DL-ROM-MethLinks
Source code for deep learning-based reduced order models for nonlinear time-dependent parametrized PDEs. Available on doi.org/10.1007/s10915-021-01462-7.
☆25Updated last year
Alternatives and similar repositories for DL-ROM-Meth
Users that are interested in DL-ROM-Meth are comparing it to the libraries listed below
Sorting:
- Source code for POD-DL-ROM: enhancing deep learning-based reduced order models for nonlinear parametrized PDEs by proper orthogonal decom…☆32Updated last year
- POD-PINN code and manuscript☆52Updated 8 months ago
- Python tools for non-intrusive reduced order modeling☆19Updated 4 months ago
- TensorFlow 2.0 implementation of Yibo Yang, Paris Perdikaris’s adversarial Uncertainty Quantification in Physics Informed Neural Networks…☆20Updated 2 years ago
- Surrogate Modeling for Fluid Flows Based on Physics-Constrained Label-Free Deep Learning☆89Updated last year
- Standardized Non-Intrusive Reduced Order Modeling☆12Updated 2 years ago
- Multifidelity deep neural operators for efficient learning of partial differential equations with application to fast inverse design of n…☆35Updated 2 years ago
- ☆21Updated 4 years ago
- Source code for deep learning-based reduced order models in cardiac electrophysiology. Available on doi.org/10.1371/journal.pone.0239416.☆15Updated last year
- XPINN code written in TensorFlow 2☆28Updated 2 years ago
- Physics-Constrained Bayesian Neural Network for Fluid Flow Reconstruction with Sparse and Noisy Data☆49Updated 5 years ago
- Physics-Informed Neural Networks for solving PDEs (bachelor project)☆10Updated 2 years ago
- Proper Orthogonal Decomposition - Radial Basis Function (POD-RBF) Network☆67Updated last year
- Physics-guided neural network framework for elastic plates☆45Updated 3 years ago
- Multi-fidelity reduced-order surrogate modeling☆24Updated last month
- Sparse Physics-based and Interpretable Neural Networks☆50Updated 3 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
- This repository contains the simple source codes of "Machine-learning-based reduced-order modeling for unsteady flows around bluff bodies…☆16Updated 4 years ago
- ☆11Updated last year
- Code for "Robust flow field reconstruction from limited measurements vis sparse representation" (J. Callaham, K. Maeda, and S. Brunton 20…☆14Updated 6 years ago
- Leaning Proper Orthogonal Decomposition coefficients using Deep Neural Networks.☆10Updated 5 years ago
- Non-intrusive reduced order models using proper orthogonal decomposition (POD) and radial basis function (RBF) interpolation for shallow …☆19Updated 4 years ago
- Finite Volume PINNs for Hyperbolic Conservation Laws & Compressible Flow☆18Updated 2 years ago
- GCA-ROM is a library which implements graph convolutional autoencoder architecture as a nonlinear model order reduction strategy.☆36Updated last month
- ☆25Updated 7 years ago
- PECANNs: Physics and Equality Constrained Artificial Neural Networks☆23Updated 2 years ago
- Sample codes of CNN-SINDy based reduced-order modeling for fluid flows by Fukami et al., JFM 2021.☆26Updated 3 years ago
- Discontinuity Computing Using Physics-Informed Neural Network☆24Updated last year
- Python codes for Locally Adaptive Activation Function (LAAF) used in deep neural networks. Please cite this work as "A D Jagtap, K Kawa…☆41Updated 2 years ago
- Python code to calculate proper orthogonal decomposition modes (aka principal components), which are then used to generate reduced order …☆37Updated 10 years ago