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:
- POD-PINN code and manuscript☆57Updated last year
- A collection of Jupyter notebooks providing tutorials on reduced order modeling techniques like DeepONet, FNO, DL-ROM, and POD-DL-ROM. Ea…☆30Updated last year
- Dynamic weight strategy of physics-informed neural networks for the 2D Navier-Stokes equations☆14Updated 3 years ago
- Physics-guided neural network framework for elastic plates☆50Updated 3 years ago
- PECANNs: Physics and Equality Constrained Artificial Neural Networks☆24Updated 2 years ago
- Gradient-based adaptive sampling algorithms for self-supervising PINNs☆28Updated 2 years ago
- Code accompanying "Inverse-Dirichlet Weighting Enables Reliable Training of Physics Informed Neural Networks", Maddu et al., 2021☆14Updated 4 years ago
- Physics Informed Neural Network (PINN) for the 2D Navier-Stokes equation☆40Updated 3 years ago
- A Backward Compatible -- Physics Informed Neural Network for Allen Cahn and Cahn Hilliard Equations☆36Updated 4 years ago
- PINN Implementation for IJCAI paper, "Physics-Informed Neural Networks: Minimizing Residual Loss with Wide Networks and Effective Activat…☆20Updated last year
- This repository contains the code and models for our paper "Investigating and Mitigating Failure Modes in Physics-informed Neural Network…☆19Updated 2 years ago
- Source code of 'Deep transfer operator learning for partial differential equations under conditional shift'.☆77Updated 2 years ago
- Use of Turbulence Model (Spalart-Allmaras) with PINNs for mean flow reconstruction☆12Updated last year
- Reliable extrapolation of deep neural operators informed by physics or sparse observations☆28Updated 2 years ago
- Physics-Informed Neural Network (PINN) for Solving Coupled PDEs Governing Thermochemical Physics in Bi-Material Systems☆61Updated 5 years ago
- Multifidelity deep neural operators for efficient learning of partial differential equations with application to fast inverse design of n…☆39Updated 2 years ago
- Code of the publication "Physics informed neural networks for continuum micromechanics" published in https://doi.org/10.1016/j.cma.2022.1…☆19Updated 3 years ago
- PINNs for 2D Incompressible Navier-Stokes Equation☆58Updated last year
- Enhancing PINNs for Solving PDEs via Adaptive Collocation Point Movement and Adaptive Loss Weighting☆39Updated 2 years ago
- Burgers equation solved by PINN in PyTorch☆24Updated 4 years ago
- ☆45Updated 3 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…☆43Updated 3 years ago
- ☆16Updated 2 years ago
- Sparse Physics-based and Interpretable Neural Networks☆52Updated 4 years ago
- Surrogate Modeling for Fluid Flows Based on Physics-Constrained Label-Free Deep Learning☆94Updated 2 years ago
- Coupled-Automatic-Numerical differentiation scheme for physics-informed neural network (can-PINN)☆34Updated 2 years ago
- A pytorch implementation of several approaches using PINN to slove turbulent flow☆92Updated last year
- Source code for deep learning-based reduced order models for nonlinear time-dependent parametrized PDEs. Available on doi.org/10.1007/s10…☆27Updated 2 years ago
- An unsupervised latent/output physics-informed convolutional-LSTM network for solving partial differential equations using peridynamic di…☆31Updated 3 years ago
- Physics-informed convolutional-recurrent neural networks for solving spatiotemporal PDEs☆32Updated 4 years ago