janiechen8 / DeepLSMethodLinks
☆10Updated 4 years ago
Alternatives and similar repositories for DeepLSMethod
Users that are interested in DeepLSMethod are comparing it to the libraries listed below
Sorting:
- 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
- Physics-Constrained Bayesian Neural Network for Fluid Flow Reconstruction with Sparse and Noisy Data☆49Updated 5 years ago
- POD-PINN code and manuscript☆55Updated last year
- ☆21Updated 5 years ago
- ☆63Updated 6 years ago
- Sparse Physics-based and Interpretable Neural Networks☆52Updated 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
- Surrogate Modeling for Fluid Flows Based on Physics-Constrained Label-Free Deep Learning☆93Updated 2 years ago
- Implementation of the Deep Ritz method and the Deep Galerkin method☆61Updated 5 years ago
- DAS: A deep adaptive sampling method for solving high-dimensional partial differential equations☆38Updated last year
- Competitive Physics Informed Networks☆31Updated last year
- This repository contains the code and models for our paper "Investigating and Mitigating Failure Modes in Physics-informed Neural Network…☆19Updated 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
- ☆12Updated 2 years ago
- ☆26Updated 7 years ago
- A Backward Compatible -- Physics Informed Neural Network for Allen Cahn and Cahn Hilliard Equations☆33Updated 3 years ago
- when using, please cite "Bayesian Physics-Informed Neural Networks for real-world nonlinear dynamical systems", CMAME, https://doi.org/1…☆79Updated 3 years ago
- hp-VPINNs: variational physics-informed neural network with domain decomposition is a general framework to solve differential equations☆85Updated 3 months ago
- Physics Informed Neural Network (PINN) for Burgers' equation.☆72Updated last year
- To address some of the failure modes in training of physics informed neural networks, a Lagrangian architecture is designed to conform to…☆51Updated 2 years ago
- Deep learning library for solving differential equations on top of PyTorch.☆62Updated 5 years ago
- XPINN code written in TensorFlow 2☆28Updated 2 years ago
- ☆116Updated 6 years ago
- A Physics-Informed Neural Network for solving Burgers' equation.☆32Updated last year
- Source code of 'Deep transfer operator learning for partial differential equations under conditional shift'.☆74Updated 2 years ago
- ☆42Updated 5 years ago
- PINN, DGM and DRM☆20Updated 2 years ago
- Examplary code for NN, MFNN, DynNet, PINNs and CNN☆51Updated 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