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.
☆30Updated 4 years ago
Alternatives and similar repositories for locally-adaptive-activation-functions:
Users that are interested in locally-adaptive-activation-functions are comparing it to the libraries listed below
- 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
- Multifidelity DeepONet☆30Updated last year
- Coupled-Automatic-Numerical differentiation scheme for physics-informed neural network (can-PINN)☆26Updated last year
- POD-PINN code and manuscript☆49Updated 4 months ago
- Physics-Constrained Bayesian Neural Network for Fluid Flow Reconstruction with Sparse and Noisy Data☆48Updated 4 years ago
- ☆19Updated 4 years ago
- TensorFlow 2.0 implementation of Yibo Yang, Paris Perdikaris’s adversarial Uncertainty Quantification in Physics Informed Neural Networks…☆20Updated 2 years ago
- Physics-constrained auto-regressive convolutional neural networks for dynamical PDEs☆92Updated 2 years ago
- Gradient-based adaptive sampling algorithms for self-supervising PINNs☆24Updated last year
- PECANNs: Physics and Equality Constrained Artificial Neural Networks☆20Updated last year
- DeepONet extrapolation☆26Updated last year
- Sparse Physics-based and Interpretable Neural Networks☆48Updated 3 years ago
- Discontinuity Computing Using Physics-Informed Neural Network☆23Updated 11 months ago
- Theory-guided physics-informed neural networks for boundary layer problems with singular perturbation☆16Updated 2 years ago
- ☆53Updated 2 years ago
- XPINN code written in TensorFlow 2☆27Updated 2 years ago
- ☆26Updated 2 years ago
- Variational Neural Networks for the Solution of Partial Differential Equations☆8Updated 5 years ago
- gPINN: Gradient-enhanced physics-informed neural networks☆84Updated 2 years ago
- PhyGeoNet: Physics-Informed Geometry-Adaptive Convolutional Neural Networks for Solving Parametric PDEs on Irregular Domain☆84Updated 4 years ago
- The unsupervised learning problem trains a diffeomorphic spatio-temporal grid, that registers the output sequence of the PDEs onto a non-…☆19Updated 2 years ago
- Source code of 'Deep transfer operator learning for partial differential equations under conditional shift'.☆69Updated last year
- Deep learning framework for model reduction of dynamical systems☆21Updated 4 years ago
- 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
- Original implementation of fast PINN optimization with RBA weights☆49Updated 5 months ago
- Competitive Physics Informed Networks☆27Updated 6 months ago
- This repository contains the code and models for our paper "Investigating and Mitigating Failure Modes in Physics-informed Neural Network…☆18Updated last year
- ☆62Updated 5 years ago
- Dimensionless learning codes for our paper called "Data-driven discovery of dimensionless numbers and governing laws from scarce measurem…☆36Updated 9 months ago
- A sequential DeepONet model implementation that uses a recurrent neural network (GRU and LSTM) in the branch and a feed-forward neural ne…☆13Updated 10 months ago