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☆26Updated 4 years ago
- Multi-fidelity regression with neural networks☆15Updated 11 months ago
- ☆64Updated 2 years ago
- Physics-Constrained Bayesian Neural Network for Fluid Flow Reconstruction with Sparse and Noisy Data☆49Updated 5 years ago
- Surrogate Modeling for Fluid Flows Based on Physics-Constrained Label-Free Deep Learning☆92Updated 2 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
- PECANNs: Physics and Equality Constrained Artificial Neural Networks☆24Updated 2 years ago
- Pytorch implementation of Bayesian physics-informed neural networks☆64Updated 4 years ago
- ☆63Updated 6 years ago
- Physics-constrained deep learning for high-dimensional surrogate modeling and uncertainty quantification without labeled data☆150Updated 6 years ago
- POD-PINN code and manuscript☆54Updated 11 months ago
- ☆40Updated 2 years ago
- Source code of 'Deep transfer operator learning for partial differential equations under conditional shift'.☆74Updated 2 years ago
- Gradient-based adaptive sampling algorithms for self-supervising PINNs☆27Updated 2 years ago
- PhyGeoNet: Physics-Informed Geometry-Adaptive Convolutional Neural Networks for Solving Parametric PDEs on Irregular Domain☆88Updated 4 years ago
- Deep learning library for solving differential equations on top of PyTorch.☆61Updated 5 years ago
- ☆49Updated last year
- A collection of Jupyter notebooks providing tutorials on reduced order modeling techniques like DeepONet, FNO, DL-ROM, and POD-DL-ROM. Ea…☆25Updated 9 months ago
- Gradient-enhanced physics-informed neural networks for forward and inverse PDE problems☆98Updated 3 years ago
- Physics Informed Fourier Neural Operator☆23Updated 11 months ago
- Sparse Physics-based and Interpretable Neural Networks☆52Updated 4 years ago
- This repository contains the files used in the paper " Reduced-order Model for Fluid Flows via Neural Ordinary Differential Equations"☆18Updated 2 years ago
- Implementing a physics-informed DeepONet from scratch☆47Updated 2 years ago
- ☆99Updated 4 years ago
- Physcial Informed Extreme Learning Machine(PIELM) method to solve PDEs, such as Possion problem☆15Updated 10 months ago
- ☆55Updated 3 years ago
- Reliable extrapolation of deep neural operators informed by physics or sparse observations☆27Updated 2 years ago
- ☆116Updated 6 years ago
- Bayesian deep convolutional encoder-decoder networks for surrogate modeling and uncertainty quantification☆106Updated 5 years ago
- ☆131Updated 3 years ago