Pongpisit-Thanasutives / Multi-task-Physics-informed-neural-networksLinks
Multi-task physics-informed neural networks
☆25Updated 3 years ago
Alternatives and similar repositories for Multi-task-Physics-informed-neural-networks
Users that are interested in Multi-task-Physics-informed-neural-networks are comparing it to the libraries listed below
Sorting:
- Boosting the training of physics informed neural networks with transfer learning☆27Updated 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…☆43Updated 2 years ago
- Physics-Constrained Bayesian Neural Network for Fluid Flow Reconstruction with Sparse and Noisy Data☆50Updated 5 years ago
- Multi-fidelity regression with neural networks☆16Updated 2 months ago
- PECANNs: Physics and Equality Constrained Artificial Neural Networks☆24Updated 2 years ago
- ☆68Updated 3 years ago
- POD-PINN code and manuscript☆57Updated last year
- ☆63Updated 6 years ago
- Code accompanying "Inverse-Dirichlet Weighting Enables Reliable Training of Physics Informed Neural Networks", Maddu et al., 2021☆14Updated 4 years ago
- Pytorch implementation of Bayesian physics-informed neural networks☆69Updated 4 years ago
- Surrogate Modeling for Fluid Flows Based on Physics-Constrained Label-Free Deep Learning☆93Updated 2 years ago
- ☆40Updated 2 years ago
- Gradient-based adaptive sampling algorithms for self-supervising PINNs☆28Updated 2 years ago
- Physics-constrained deep learning for high-dimensional surrogate modeling and uncertainty quantification without labeled data☆150Updated 6 years ago
- PhyGeoNet: Physics-Informed Geometry-Adaptive Convolutional Neural Networks for Solving Parametric PDEs on Irregular Domain☆91Updated 4 years ago
- Source code of 'Deep transfer operator learning for partial differential equations under conditional shift'.☆75Updated 2 years ago
- This repository contains the files used in the paper " Reduced-order Model for Fluid Flows via Neural Ordinary Differential Equations"☆19Updated 2 years ago
- Physics-Informed Neural Networks for solving PDEs (bachelor project)☆10Updated 2 years ago
- Implementation of PINNs in TensorFlow 2☆81Updated last month
- Reliable extrapolation of deep neural operators informed by physics or sparse observations☆28Updated 2 years ago
- This repository contains the code and models for our paper "Investigating and Mitigating Failure Modes in Physics-informed Neural Network…☆19Updated 2 years ago
- Competitive Physics Informed Networks☆32Updated last year
- Gradient-enhanced physics-informed neural networks for forward and inverse PDE problems☆107Updated 3 years ago
- ☆38Updated 2 years ago
- Deep learning library for solving differential equations on top of PyTorch.☆62Updated 5 years ago
- Towards Physics-informed Deep Learning for Turbulent Flow Prediction☆27Updated 4 years ago
- ☆54Updated 3 years ago
- when using, please cite "Bayesian Physics-Informed Neural Networks for real-world nonlinear dynamical systems", CMAME, https://doi.org/1…☆83Updated 3 years ago
- Physics-Informed Neural Network (PINN) for Solving Coupled PDEs Governing Thermochemical Physics in Bi-Material Systems☆60Updated 5 years ago
- Bayesian deep convolutional encoder-decoder networks for surrogate modeling and uncertainty quantification☆107Updated 5 years ago