Jianxun-Wang / Physics-constrained-Bayesian-deep-learning
Physics-Constrained Bayesian Neural Network for Fluid Flow Reconstruction with Sparse and Noisy Data
☆48Updated 4 years ago
Alternatives and similar repositories for Physics-constrained-Bayesian-deep-learning:
Users that are interested in Physics-constrained-Bayesian-deep-learning are comparing it to the libraries listed below
- ☆62Updated 5 years ago
- POD-PINN code and manuscript☆49Updated 4 months ago
- Multi-fidelity reduced-order surrogate modeling☆19Updated 3 months ago
- Surrogate Modeling for Fluid Flows Based on Physics-Constrained Label-Free Deep Learning☆86Updated last year
- This repository contains the files used in the paper " Reduced-order Model for Fluid Flows via Neural Ordinary Differential Equations"☆18Updated 2 years ago
- when using, please cite "Bayesian Physics-Informed Neural Networks for real-world nonlinear dynamical systems", CMAME, https://doi.org/1…☆67Updated 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…☆39Updated 2 years ago
- TensorFlow 2.0 implementation of Yibo Yang, Paris Perdikaris’s adversarial Uncertainty Quantification in Physics Informed Neural Networks…☆20Updated 2 years ago
- PhyGeoNet: Physics-Informed Geometry-Adaptive Convolutional Neural Networks for Solving Parametric PDEs on Irregular Domain☆84Updated 4 years ago
- Sparse Physics-based and Interpretable Neural Networks☆48Updated 3 years ago
- Pytorch implementation of Bayesian physics-informed neural networks☆56Updated 3 years ago
- XPINN code written in TensorFlow 2☆27Updated 2 years ago
- DeepONet extrapolation☆26Updated 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 2 months ago
- Multifidelity DeepONet☆30Updated last year
- Sample codes of CNN-SINDy based reduced-order modeling for fluid flows by Fukami et al., JFM 2021.☆25Updated 3 years ago
- ☆13Updated 5 years ago
- ☆19Updated 4 years ago
- ☆28Updated last year
- A python implementation of Physics-informed Spline Learning for nonlinear dynamics discovery.☆25Updated 3 years ago
- ☆53Updated 2 years ago
- Examplary code for NN, MFNN, DynNet, PINNs and CNN☆49Updated 3 years ago
- Coupled-Automatic-Numerical differentiation scheme for physics-informed neural network (can-PINN)☆26Updated last year
- One-Shot Transfer Learning of PINNs☆10Updated last year
- ☆36Updated last year
- Gradient-based adaptive sampling algorithms for self-supervising PINNs☆24Updated last year
- Source code for deep learning-based reduced order models for nonlinear time-dependent parametrized PDEs. Available on doi.org/10.1007/s10…☆24Updated last year
- Competitive Physics Informed Networks☆27Updated 6 months ago
- B-PINN - Jax - HMC tutorial☆17Updated 2 years ago
- Boosting the training of physics informed neural networks with transfer learning☆26Updated 3 years ago