XuhuiM / Multi-Fidelity-DNNs-PINNsLinks
☆38Updated 2 years ago
Alternatives and similar repositories for Multi-Fidelity-DNNs-PINNs
Users that are interested in Multi-Fidelity-DNNs-PINNs are comparing it to the libraries listed below
Sorting:
- ☆42Updated 2 years ago
- Multi-fidelity reduced-order surrogate modeling☆25Updated 3 months ago
- multi-fidelity neural network☆20Updated 2 years ago
- POD-PINN code and manuscript☆53Updated 10 months ago
- Multi-fidelity regression with neural networks☆15Updated 10 months ago
- Multifidelity deep neural operators for efficient learning of partial differential equations with application to fast inverse design of n…☆35Updated 2 years ago
- Pytorch implementation of Bayesian physics-informed neural networks☆63Updated 4 years ago
- Multi-fidelity Gaussian Process☆27Updated 4 years ago
- Physics-Constrained Bayesian Neural Network for Fluid Flow Reconstruction with Sparse and Noisy Data☆49Updated 5 years ago
- Surrogate Modeling for Fluid Flows Based on Physics-Constrained Label-Free Deep Learning☆91Updated 2 years ago
- Examplary code for NN, MFNN, DynNet, PINNs and CNN☆51Updated 4 years ago
- Sparse Physics-based and Interpretable Neural Networks☆52Updated 4 years ago
- ☆63Updated 6 years ago
- Source code of 'Deep transfer operator learning for partial differential equations under conditional shift'.☆73Updated 2 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…☆42Updated 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 2 years ago
- Multi-fidelity probability machine learning☆19Updated 8 months ago
- ☆41Updated 3 years ago
- Physics-guided neural network framework for elastic plates☆46Updated 3 years ago
- A Backward Compatible -- Physics Informed Neural Network for Allen Cahn and Cahn Hilliard Equations☆33Updated 3 years ago
- ☆19Updated last year
- This repository comprises Jupyter Notebooks that serve as supplementary material to the journal article titled "Review of Multifidelity M…☆10Updated 2 years ago
- Physics-informed graph neural Galerkin networks: A unified framework for solving PDE-governed forward and inverse problems☆56Updated 3 years ago
- Physics-Informed Neural Network (PINN) for Solving Coupled PDEs Governing Thermochemical Physics in Bi-Material Systems☆58Updated 4 years ago
- when using, please cite "Bayesian Physics-Informed Neural Networks for real-world nonlinear dynamical systems", CMAME, https://doi.org/1…☆77Updated 3 years ago
- ☆64Updated 2 years ago
- Examples implementing physics-informed neural networks (PINN) in Pytorch☆76Updated 4 years ago
- PhyGeoNet: Physics-Informed Geometry-Adaptive Convolutional Neural Networks for Solving Parametric PDEs on Irregular Domain☆88Updated 4 years ago
- Reproduce the first two numerical experiments(Pytorch)☆26Updated 5 years ago
- Sample codes of CNN-SINDy based reduced-order modeling for fluid flows by Fukami et al., JFM 2021.☆26Updated 4 years ago