Extended Physics-Informed Neural Networks (XPINNs): A Generalized Space-Time Domain Decomposition Based Deep Learning Framework for Nonlinear Partial Differential Equations
☆246Feb 1, 2023Updated 3 years ago
Alternatives and similar repositories for XPINNs
Users that are interested in XPINNs are comparing it to the libraries listed below
Sorting:
- We propose a conservative physics-informed neural network (cPINN) on decompose domains for nonlinear conservation laws. The conservation …☆77Feb 1, 2023Updated 3 years ago
- XPINN code written in TensorFlow 2☆28Feb 1, 2023Updated 3 years ago
- hp-VPINNs: variational physics-informed neural network with domain decomposition is a general framework to solve differential equations☆88Aug 26, 2025Updated 6 months ago
- ☆244Oct 14, 2021Updated 4 years ago
- Implementation of the paper "Self-Adaptive Physics-Informed Neural Networks using a Soft Attention Mechanism" [AAAI-MLPS 2021]☆280Oct 12, 2021Updated 4 years ago
- Gradient-enhanced physics-informed neural networks for forward and inverse PDE problems☆108Apr 15, 2022Updated 3 years ago
- Solve forward and inverse problems related to partial differential equations using finite basis physics-informed neural networks (FBPINNs…☆527Nov 27, 2025Updated 3 months ago
- ☆169Jun 27, 2022Updated 3 years ago
- ☆207Feb 16, 2024Updated 2 years ago
- A place to share problems solved with SciANN☆305Nov 6, 2023Updated 2 years ago
- PhyGeoNet: Physics-Informed Geometry-Adaptive Convolutional Neural Networks for Solving Parametric PDEs on Irregular Domain☆92Jan 24, 2021Updated 5 years ago
- Demo code for PPINN paper: https://www.sciencedirect.com/science/article/pii/S0045782520304357☆11Oct 23, 2020Updated 5 years ago
- physics-informed neural network for elastodynamics problem☆157Jan 20, 2022Updated 4 years ago
- Deep learning for Engineers - Physics Informed Deep Learning☆362Dec 20, 2023Updated 2 years ago
- Must-read Papers on Physics-Informed Neural Networks.☆1,434Dec 8, 2023Updated 2 years ago
- Physics Informed Neural Network (PINN) for the wave equation.☆202Jul 16, 2020Updated 5 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…☆44Feb 1, 2023Updated 3 years ago
- POD-PINN code and manuscript☆58Nov 10, 2024Updated last year
- Hidden Fluid Mechanics☆356Jan 30, 2023Updated 3 years ago
- Physics Informed Deep Learning: Data-driven Solutions and Discovery of Nonlinear Partial Differential Equations☆5,611Feb 11, 2026Updated 3 weeks ago
- ☆69Nov 15, 2022Updated 3 years ago
- Gradient-based adaptive sampling algorithms for self-supervising PINNs☆28May 8, 2023Updated 2 years ago
- Competitive Physics Informed Networks☆32Sep 21, 2024Updated last year
- Physics Informed Machine Learning Tutorials (Pytorch and Jax)☆647Feb 28, 2026Updated last week
- PyTorch Implementation of Physics-informed Neural Networks☆703May 20, 2024Updated last year
- Code accompanying the manuscript "Augmented Physics-Informed Neural Networks (APINNs): A gating network-based soft domain decomposition m…☆16Sep 18, 2023Updated 2 years ago
- ☆111Oct 16, 2021Updated 4 years ago
- Learning nonlinear operators via DeepONet based on the universal approximation theorem of operators☆765Jun 25, 2022Updated 3 years ago
- A library for scientific machine learning and physics-informed learning☆3,907Mar 1, 2026Updated last week
- Physics-informed convolutional-recurrent neural networks for solving spatiotemporal PDEs☆32Dec 24, 2021Updated 4 years ago
- Surrogate Modeling for Fluid Flows Based on Physics-Constrained Label-Free Deep Learning☆95Aug 17, 2023Updated 2 years ago
- ☆391Dec 3, 2022Updated 3 years ago
- ☆512Apr 1, 2025Updated 11 months ago
- [NeurIPS 2024] Codebase for PINNacle: A Comprehensive Benchmark of Physics-Informed Neural Networks for Solving PDEs.☆401Feb 11, 2026Updated 3 weeks ago
- ☆26Oct 15, 2020Updated 5 years ago
- A comprehensive study of non-adaptive and residual-based adaptive sampling for physics-informed neural networks☆100Oct 24, 2022Updated 3 years ago
- Physics-constrained auto-regressive convolutional neural networks for dynamical PDEs☆93May 11, 2022Updated 3 years ago
- To address some of the failure modes in training of physics informed neural networks, a Lagrangian architecture is designed to conform to…☆52Jan 10, 2023Updated 3 years ago
- PINN in solving Navier–Stokes equation☆126Jun 7, 2020Updated 5 years ago