weipengOO98 / PDPINNLinks
☆15Updated 5 years ago
Alternatives and similar repositories for PDPINN
Users that are interested in PDPINN are comparing it to the libraries listed below
Sorting:
- Physics-Constrained Bayesian Neural Network for Fluid Flow Reconstruction with Sparse and Noisy Data☆49Updated 5 years ago
- ☆63Updated 6 years ago
- Numerical Gaussian Processes for Time-dependent and Non-linear Partial Differential Equations☆69Updated 5 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
- DAS: A deep adaptive sampling method for solving high-dimensional partial differential equations☆38Updated 10 months ago
- Surrogate Modeling for Fluid Flows Based on Physics-Constrained Label-Free Deep Learning☆91Updated 2 years ago
- This is the repository for the code used in the ICML23 paper called "Achieving High Accuracy with PINNs via Energy Natural Gradient Desce…☆22Updated 11 months ago
- POD-PINN code and manuscript☆53Updated 11 months ago
- Deep learning framework for model reduction of dynamical systems☆21Updated 4 years ago
- ATHENA: Advanced Techniques for High dimensional parameter spaces to Enhance Numerical Analysis☆55Updated 2 years ago
- ☆39Updated 2 years ago
- Methods and code for J. L. Callaham, J. N. Kutz, B. W. Brunton, and S. L. Brunton (2020)☆59Updated 4 years ago
- ☆21Updated 4 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
- ☆42Updated 5 years ago
- Sparse Physics-based and Interpretable Neural Networks☆52Updated 4 years ago
- when using, please cite "Bayesian Physics-Informed Neural Networks for real-world nonlinear dynamical systems", CMAME, https://doi.org/1…☆78Updated 3 years ago
- ☆54Updated 3 years ago
- Multistep Neural Networks for Data-driven Discovery of Nonlinear Dynamical Systems☆63Updated 5 years ago
- ☆26Updated 7 years ago
- Physics-constrained auto-regressive convolutional neural networks for dynamical PDEs☆93Updated 3 years ago
- This repository contains the files used in the paper " Reduced-order Model for Fluid Flows via Neural Ordinary Differential Equations"☆18Updated 2 years ago
- PhyGeoNet: Physics-Informed Geometry-Adaptive Convolutional Neural Networks for Solving Parametric PDEs on Irregular Domain☆88Updated 4 years ago
- ☆14Updated 3 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
- Tutorial on Gaussian Processes☆62Updated 5 years ago
- Multi-fidelity reduced-order surrogate modeling☆25Updated 3 months ago
- Enhancing Dynamic Mode Decomposition using Autoencoder Networks.☆33Updated 4 years ago
- Source code for deep learning-based reduced order models for nonlinear time-dependent parametrized PDEs. Available on doi.org/10.1007/s10…☆25Updated 2 years ago
- ☆12Updated last week