akapet00 / locally-adaptive-activation-functions
Simplified implementation of locally adaptive activation functions (LAAF) with slope recovery for deep and physics-informed neural networks (PINNs) in PyTorch.
☆29Updated 3 years ago
Related projects: ⓘ
- Python codes for Locally Adaptive Activation Function (LAAF) used in deep neural networks. Please cite this work as "A D Jagtap, K Kawa…☆37Updated last year
- POD-PINN code and manuscript☆44Updated 3 years ago
- Sparse Physics-based and Interpretable Neural Networks☆43Updated 2 years ago
- Deep learning framework for model reduction of dynamical systems☆21Updated 3 years ago
- Multifidelity DeepONet☆25Updated last year
- Gradient-based adaptive sampling algorithms for self-supervising PINNs☆20Updated last year
- when using, please cite "Bayesian Physics-Informed Neural Networks for real-world nonlinear dynamical systems", CMAME, https://doi.org/1…☆52Updated 2 years ago
- ☆17Updated 3 years ago
- Coupled-Automatic-Numerical differentiation scheme for physics-informed neural network (can-PINN)☆23Updated 9 months ago
- TensorFlow 2.0 implementation of Yibo Yang, Paris Perdikaris’s adversarial Uncertainty Quantification in Physics Informed Neural Networks…☆17Updated last year
- DeepONet extrapolation☆20Updated last year
- Code for "Robust flow field reconstruction from limited measurements vis sparse representation" (J. Callaham, K. Maeda, and S. Brunton 20…☆12Updated 5 years ago
- Physics-Constrained Bayesian Neural Network for Fluid Flow Reconstruction with Sparse and Noisy Data☆42Updated 4 years ago
- Source code of 'Deep transfer operator learning for partial differential equations under conditional shift'.☆59Updated last year
- PECANNs: Physics and Equality Constrained Artificial Neural Networks☆20Updated last year
- ☆28Updated 2 years ago
- Pytorch implementation of Bayesian physics-informed neural networks☆33Updated 3 years ago
- XPINN code written in TensorFlow 2☆25Updated last year
- Variational Neural Networks for the Solution of Partial Differential Equations☆8Updated 4 years ago
- This repository contains the code and models for our paper "Investigating and Mitigating Failure Modes in Physics-informed Neural Network…☆15Updated 9 months ago
- ☆22Updated last year
- Competitive Physics Informed Networks☆26Updated last year
- Code accompanying "Inverse-Dirichlet Weighting Enables Reliable Training of Physics Informed Neural Networks", Maddu et al., 2021☆9Updated 2 years ago
- Implementation of fast PINN optimization with RBA weights☆32Updated last month
- Source code for deep learning-based reduced order models for nonlinear time-dependent parametrized PDEs. Available on doi.org/10.1007/s10…☆19Updated last year
- Physics-informed convolutional-recurrent neural networks for solving spatiotemporal PDEs☆20Updated 2 years ago
- In this repository, you will find the different python scripts to train the available models on the AirfRANS dataset proposed at the Neur…☆39Updated last year
- Source code for POD-DL-ROM: enhancing deep learning-based reduced order models for nonlinear parametrized PDEs by proper orthogonal decom…☆26Updated last year
- PhyGeoNet: Physics-Informed Geometry-Adaptive Convolutional Neural Networks for Solving Parametric PDEs on Irregular Domain☆80Updated 3 years ago
- ☆19Updated 2 years ago