SiddeshSambasivam / Physics-Informed-Neural-NetworksLinks
This repository provides a PyTorch implementation of the physics informed neural networks by M.Raissi et al.
☆11Updated 4 years ago
Alternatives and similar repositories for Physics-Informed-Neural-Networks
Users that are interested in Physics-Informed-Neural-Networks are comparing it to the libraries listed below
Sorting:
- Dynamic weight strategy of physics-informed neural networks for the 2D Navier-Stokes equations☆14Updated 3 years ago
- POD-PINN code and manuscript☆56Updated last year
- PINN Implementation for IJCAI paper, "Physics-Informed Neural Networks: Minimizing Residual Loss with Wide Networks and Effective Activat…☆20Updated last year
- PECANNs: Physics and Equality Constrained Artificial Neural Networks☆24Updated 2 years ago
- Physics Informed Neural Network (PINN) for the 2D Navier-Stokes equation☆36Updated 3 years ago
- This repository contains the code and models for our paper "Investigating and Mitigating Failure Modes in Physics-informed Neural Network…☆19Updated 2 years ago
- A collection of Jupyter notebooks providing tutorials on reduced order modeling techniques like DeepONet, FNO, DL-ROM, and POD-DL-ROM. Ea…☆27Updated 10 months ago
- Deep finite volume method☆21Updated last year
- Physics-guided neural network framework for elastic plates☆48Updated 3 years ago
- A Backward Compatible -- Physics Informed Neural Network for Allen Cahn and Cahn Hilliard Equations☆35Updated 3 years ago
- ☆12Updated last year
- Enhancing PINNs for Solving PDEs via Adaptive Collocation Point Movement and Adaptive Loss Weighting☆38Updated 2 years ago
- ☆29Updated 3 years ago
- Competitive Physics Informed Networks☆32Updated last year
- Gradient-based adaptive sampling algorithms for self-supervising PINNs☆28Updated 2 years ago
- ☆13Updated 2 years ago
- ☆12Updated last week
- Surrogate Modeling for Fluid Flows Based on Physics-Constrained Label-Free Deep Learning☆93Updated 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
- Physics-informed neural networks for highly compressible flows 🧠🌊☆27Updated 2 years ago
- Sparse Physics-based and Interpretable Neural Networks☆52Updated 4 years ago
- Physcial Informed Extreme Learning Machine(PIELM) method to solve PDEs, such as Possion problem☆15Updated last year
- Reliable extrapolation of deep neural operators informed by physics or sparse observations☆28Updated 2 years ago
- Transformed Generative Pre-Trained Physics-Informed Neural Networks (TGPT-PINN), a framework that extends Physics-Informed Neural Network…☆18Updated last year
- ☆44Updated 3 years ago
- Code accompanying "Inverse-Dirichlet Weighting Enables Reliable Training of Physics Informed Neural Networks", Maddu et al., 2021☆14Updated 4 years ago
- PhyGeoNet: Physics-Informed Geometry-Adaptive Convolutional Neural Networks for Solving Parametric PDEs on Irregular Domain☆88Updated 4 years ago
- Coupled-Automatic-Numerical differentiation scheme for physics-informed neural network (can-PINN)☆32Updated 2 years ago
- Physics-informed convolutional-recurrent neural networks for solving spatiotemporal PDEs☆31Updated 3 years ago
- Simple demo on implementing data driven and physics informed Deep O Nets in pytorch☆19Updated last year