comp-physics / CPINN
Competitive Physics Informed Networks
☆27Updated 6 months ago
Alternatives and similar repositories for CPINN:
Users that are interested in CPINN are comparing it to the libraries listed below
- DeepONet extrapolation☆27Updated last year
- POD-PINN code and manuscript☆50Updated 5 months ago
- Multifidelity DeepONet☆30Updated 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…☆39Updated 2 years ago
- MIONet: Learning multiple-input operators via tensor product☆33Updated 2 years ago
- ☆27Updated 2 years ago
- Sparse Physics-based and Interpretable Neural Networks☆48Updated 3 years ago
- XPINN code written in TensorFlow 2☆27Updated 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 2 months ago
- Coupled-Automatic-Numerical differentiation scheme for physics-informed neural network (can-PINN)☆28Updated last year
- This repository contains the code and models for our paper "Investigating and Mitigating Failure Modes in Physics-informed Neural Network…☆18Updated last year
- To address some of the failure modes in training of physics informed neural networks, a Lagrangian architecture is designed to conform to…☆47Updated 2 years ago
- Gradient-based adaptive sampling algorithms for self-supervising PINNs☆24Updated last year
- PhyGeoNet: Physics-Informed Geometry-Adaptive Convolutional Neural Networks for Solving Parametric PDEs on Irregular Domain☆84Updated 4 years ago
- ☆53Updated 2 years ago
- Discontinuity Computing Using Physics-Informed Neural Network☆23Updated 11 months ago
- Source code of 'Deep transfer operator learning for partial differential equations under conditional shift'.☆70Updated last year
- PDE Preserved Neural Network☆46Updated 9 months ago
- Physics-Constrained Bayesian Neural Network for Fluid Flow Reconstruction with Sparse and Noisy Data☆48Updated 4 years ago
- PINNs for 2D Incompressible Navier-Stokes Equation☆44Updated 10 months ago
- gPINN: Gradient-enhanced physics-informed neural networks☆86Updated 2 years ago
- Physics-informed graph neural Galerkin networks: A unified framework for solving PDE-governed forward and inverse problems☆50Updated 3 years ago
- Theory-guided physics-informed neural networks for boundary layer problems with singular perturbation☆17Updated 2 years ago
- ☆19Updated 4 years ago
- GCA-ROM is a library which implements graph convolutional autoencoder architecture as a nonlinear model order reduction strategy.☆35Updated this week
- A sequential DeepONet model implementation that uses a recurrent neural network (GRU and LSTM) in the branch and a feed-forward neural ne…☆14Updated 11 months ago
- Yet another PINN implementation☆20Updated 9 months ago
- Multi-fidelity reduced-order surrogate modeling☆21Updated 4 months ago
- Surrogate Modeling for Fluid Flows Based on Physics-Constrained Label-Free Deep Learning☆87Updated last year
- Original implementation of fast PINN optimization with RBA weights☆50Updated 5 months ago