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:
- POD-PINN code and manuscript☆52Updated 9 months ago
- Physics-Constrained Bayesian Neural Network for Fluid Flow Reconstruction with Sparse and Noisy Data☆49Updated 5 years ago
- This repository contains the code and models for our paper "Investigating and Mitigating Failure Modes in Physics-informed Neural Network…☆18Updated last year
- ☆21Updated 4 years ago
- ☆63Updated 6 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…☆41Updated 2 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☆89Updated last year
- DAS: A deep adaptive sampling method for solving high-dimensional partial differential equations☆38Updated 8 months ago
- Sparse Physics-based and Interpretable Neural Networks☆50Updated 3 years ago
- ☆11Updated last year
- PhyGeoNet: Physics-Informed Geometry-Adaptive Convolutional Neural Networks for Solving Parametric PDEs on Irregular Domain☆87Updated 4 years ago
- A Physics-Informed Neural Network for solving Burgers' equation.☆33Updated last year
- ☆42Updated 5 years ago
- when using, please cite "Bayesian Physics-Informed Neural Networks for real-world nonlinear dynamical systems", CMAME, https://doi.org/1…☆74Updated 3 years ago
- A Deep Learning based Approach to Reduced Order Modeling for Turbulent Flow Control using LSTM Neural Networks. arXiv:1804.09269☆43Updated 7 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
- Deep learning library for solving differential equations on top of PyTorch.☆61Updated 5 years ago
- ☆116Updated 6 years ago
- Implementation of the Deep Ritz method and the Deep Galerkin method☆58Updated 5 years ago
- To address some of the failure modes in training of physics informed neural networks, a Lagrangian architecture is designed to conform to…☆49Updated 2 years ago
- A Backward Compatible -- Physics Informed Neural Network for Allen Cahn and Cahn Hilliard Equations☆32Updated 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
- PINN, DGM and DRM☆20Updated 2 years ago
- Code for the FiniteNet ICML Paper☆18Updated 5 years ago
- Physics-constrained auto-regressive convolutional neural networks for dynamical PDEs☆93Updated 3 years ago
- ☆54Updated 2 years ago
- Companion code for "Solving Nonlinear and High-Dimensional Partial Differential Equations via Deep Learning" by A. Al-Aradi, A. Correia, …☆118Updated 6 years ago
- Original implementation of fast PINN optimization with RBA weights☆57Updated 3 months ago
- This is the repository for the code used in the ICML23 paper called "Achieving High Accuracy with PINNs via Energy Natural Gradient Desce…☆20Updated 9 months ago