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:
- PECANNs: Physics and Equality Constrained Artificial Neural Networks☆24Updated 2 years ago
- Transformed Generative Pre-Trained Physics-Informed Neural Networks (TGPT-PINN), a framework that extends Physics-Informed Neural Network…☆17Updated last year
- Dynamic weight strategy of physics-informed neural networks for the 2D Navier-Stokes equations☆12Updated 3 years ago
- POD-PINN code and manuscript☆53Updated 10 months ago
- ☆12Updated last year
- Physics-guided neural network framework for elastic plates☆46Updated 3 years ago
- A collection of Jupyter notebooks providing tutorials on reduced order modeling techniques like DeepONet, FNO, DL-ROM, and POD-DL-ROM. Ea…☆25Updated 8 months ago
- Reliable extrapolation of deep neural operators informed by physics or sparse observations☆27Updated 2 years ago
- DON-LSTM: Multi-Resolution Learning with DeepONets and Long-Short Term Memory Neural Networks☆11Updated 3 weeks ago
- Coupled-Automatic-Numerical differentiation scheme for physics-informed neural network (can-PINN)☆32Updated last year
- Yet another PINN implementation☆20Updated last year
- Multifidelity deep neural operators for efficient learning of partial differential equations with application to fast inverse design of n…☆35Updated 2 years ago
- This repository contains the code and models for our paper "Investigating and Mitigating Failure Modes in Physics-informed Neural Network…☆19Updated last year
- Gradient-based adaptive sampling algorithms for self-supervising PINNs☆27Updated 2 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
- Burgers equation solved by PINN in PyTorch☆24Updated 4 years ago
- Sparse Physics-based and Interpretable Neural Networks☆52Updated 4 years ago
- Physics-informed neural networks for highly compressible flows 🧠🌊☆27Updated last year
- Physics Informed Neural Network (PINN) for the 2D Navier-Stokes equation☆31Updated 3 years ago
- ☆12Updated 9 months ago
- parallel PINNs; RANS equations; spatiotemporal parallel; PINNs☆33Updated last year
- 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
- ☆14Updated 2 years ago
- Surrogate Modeling for Fluid Flows Based on Physics-Constrained Label-Free Deep Learning☆91Updated 2 years ago
- Competitive Physics Informed Networks☆31Updated last year
- PINNs for 2D Incompressible Navier-Stokes Equation☆53Updated last year
- An implementation of Physics-Informed Neural Networks (PINNs) to solve various forward and inverse problems for the 1 dimensional wave eq…☆40Updated 3 years ago
- Physics Informed Neural Network (PINN) for Burgers' equation.☆71Updated last year
- A Backward Compatible -- Physics Informed Neural Network for Allen Cahn and Cahn Hilliard Equations☆33Updated 3 years ago
- ☆12Updated 2 months ago