comp-physics / CPINNLinks
Competitive Physics Informed Networks
☆31Updated last year
Alternatives and similar repositories for CPINN
Users that are interested in CPINN are comparing it to the libraries listed below
Sorting:
- Reliable extrapolation of deep neural operators informed by physics or sparse observations☆27Updated 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
- Gradient-enhanced physics-informed neural networks for forward and inverse PDE problems☆99Updated 3 years ago
- POD-PINN code and manuscript☆53Updated 10 months ago
- XPINN code written in TensorFlow 2☆28Updated 2 years ago
- PINNs for 2D Incompressible Navier-Stokes Equation☆53Updated last year
- Sparse Physics-based and Interpretable Neural Networks☆52Updated 4 years ago
- ☆54Updated 2 years ago
- Surrogate Modeling for Fluid Flows Based on Physics-Constrained Label-Free Deep Learning☆91Updated 2 years ago
- PhyGeoNet: Physics-Informed Geometry-Adaptive Convolutional Neural Networks for Solving Parametric PDEs on Irregular Domain☆88Updated 4 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…☆42Updated 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…☆25Updated 8 months ago
- MIONet: Learning multiple-input operators via tensor product☆38Updated 2 years ago
- hp-VPINNs: variational physics-informed neural network with domain decomposition is a general framework to solve differential equations☆83Updated last month
- Source code of 'Deep transfer operator learning for partial differential equations under conditional shift'.☆73Updated 2 years ago
- We propose a conservative physics-informed neural network (cPINN) on decompose domains for nonlinear conservation laws. The conservation …☆74Updated 2 years ago
- Discontinuity Computing Using Physics-Informed Neural Network☆26Updated last year
- ☆98Updated 3 years ago
- Yet another PINN implementation☆20Updated last year
- Multi-fidelity reduced-order surrogate modeling☆25Updated 3 months ago
- This repository contains the code and models for our paper "Investigating and Mitigating Failure Modes in Physics-informed Neural Network…☆19Updated last year
- A Backward Compatible -- Physics Informed Neural Network for Allen Cahn and Cahn Hilliard Equations☆33Updated 3 years ago
- ☆29Updated 8 months ago
- Original implementation of fast PINN optimization with RBA weights☆60Updated 3 weeks ago
- Physics-informed graph neural Galerkin networks: A unified framework for solving PDE-governed forward and inverse problems☆56Updated 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…☆50Updated 2 years ago
- Physics Informed Neural Network (PINN) for Burgers' equation.☆71Updated last year
- ☆29Updated 3 years ago
- Physics-guided neural network framework for elastic plates☆46Updated 3 years ago
- Reduced-Order Modeling of Fluid Flows with Transformers☆24Updated 2 years ago