mariusmerkle / TL-PINNsLinks
Boosting the training of physics informed neural networks with transfer learning
☆26Updated 4 years ago
Alternatives and similar repositories for TL-PINNs
Users that are interested in TL-PINNs are comparing it to the libraries listed below
Sorting:
- Gradient-based adaptive sampling algorithms for self-supervising PINNs☆27Updated 2 years ago
- Pytorch implementation of Bayesian physics-informed neural networks☆60Updated 3 years ago
- Enhancing PINNs for Solving PDEs via Adaptive Collocation Point Movement and Adaptive Loss Weighting☆35Updated 2 years ago
- ☆63Updated 2 years ago
- POD-PINN code and manuscript☆52Updated 8 months ago
- Research/development of physics-informed neural networks for dynamic systems☆25Updated 7 months ago
- Physics-guided Convolutional Neural Network☆67Updated 4 years ago
- A python implementation of Physics-informed Spline Learning for nonlinear dynamics discovery.☆26Updated 3 years ago
- ☆128Updated 2 years ago
- ☆25Updated 2 years ago
- gPINN: Gradient-enhanced physics-informed neural networks☆93Updated 3 years ago
- ☆37Updated last year
- The code for the paper Temperature field inversion of heat-source systems via physics-informed neural networks☆37Updated 2 years ago
- Original implementation of fast PINN optimization with RBA weights☆57Updated 3 months ago
- An automatic knowledge embedding framework for scientific machine learning☆23Updated 3 years ago
- Physics-guided neural network framework for elastic plates☆42Updated 3 years ago
- Surrogate Modeling for Fluid Flows Based on Physics-Constrained Label-Free Deep Learning☆88Updated last year
- ☆145Updated 3 years ago
- Non-adaptive and residual-based adaptive sampling for PINNs☆82Updated 2 years ago
- PECANNs: Physics and Equality Constrained Artificial Neural Networks☆23Updated 2 years ago
- when using, please cite "Bayesian Physics-Informed Neural Networks for real-world nonlinear dynamical systems", CMAME, https://doi.org/1…☆73Updated 3 years ago
- Physics Informed Fourier Neural Operator☆23Updated 7 months ago
- Physics-Constrained Bayesian Neural Network for Fluid Flow Reconstruction with Sparse and Noisy Data☆49Updated 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…☆40Updated 2 years ago
- Physics-informed convolutional-recurrent neural networks for solving spatiotemporal PDEs☆150Updated last year
- Physics-informed learning of governing equations from scarce data☆145Updated last year
- This repo contains a PyTorch-based AE-ConvLSTM model for fluid flow prediction. It can forecast 5–10 time steps per forward pass and over…☆24Updated last month
- This repository contains the code and models for our paper "Investigating and Mitigating Failure Modes in Physics-informed Neural Network…☆18Updated last year
- Physics-encoded recurrent convolutional neural network☆46Updated 3 years ago
- Basic implementation of physics-informed neural network with pytorch.☆71Updated 2 years ago