RizaXudayi / VarNet
Variational Neural Networks for the Solution of Partial Differential Equations
☆8Updated 5 years ago
Alternatives and similar repositories for VarNet:
Users that are interested in VarNet are comparing it to the libraries listed below
- DeepONet extrapolation☆27Updated last year
- Physics-Informed Neural Networks for solving PDEs (bachelor project)☆10Updated 2 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
- Coupled-Automatic-Numerical differentiation scheme for physics-informed neural network (can-PINN)☆28Updated last year
- XPINN code written in TensorFlow 2☆27Updated 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
- Code for "Robust flow field reconstruction from limited measurements vis sparse representation" (J. Callaham, K. Maeda, and S. Brunton 20…☆14Updated 6 years ago
- Multifidelity DeepONet☆31Updated last year
- Sparse Physics-based and Interpretable Neural Networks☆48Updated 3 years ago
- Reduced-Order Modeling of Fluid Flows with Transformers☆24Updated last year
- Gradient-based adaptive sampling algorithms for self-supervising PINNs☆25Updated last year
- Python codes for Locally Adaptive Activation Function (LAAF) used in deep neural networks. Please cite this work as "A D Jagtap, K Kawa…☆40Updated 2 years ago
- POD-PINN code and manuscript☆51Updated 5 months ago
- Discontinuity Computing Using Physics-Informed Neural Network☆24Updated last year
- ☆41Updated 2 years ago
- Code accompanying "Inverse-Dirichlet Weighting Enables Reliable Training of Physics Informed Neural Networks", Maddu et al., 2021☆11Updated 3 years ago
- ☆14Updated 3 years ago
- ☆28Updated 2 years ago
- ☆24Updated 6 years ago
- Physics-Constrained Bayesian Neural Network for Fluid Flow Reconstruction with Sparse and Noisy Data☆48Updated 4 years ago
- Accelerating Physics Informed Neural Networks (PINNs) using Meshless Discretizations☆25Updated 2 years ago
- A sequential DeepONet model implementation that uses a recurrent neural network (GRU and LSTM) in the branch and a feed-forward neural ne…☆14Updated last year
- Python tools for non-intrusive reduced order modeling☆19Updated last month
- Source code for deep learning-based reduced order models in cardiac electrophysiology. Available on doi.org/10.1371/journal.pone.0239416.☆15Updated last year
- Learning with Higher Expressive Power than Neural Networks (On Learning PDEs)☆15Updated 4 years ago
- Physics-guided neural network framework for elastic plates☆38Updated 3 years ago
- Source code for POD-DL-ROM: enhancing deep learning-based reduced order models for nonlinear parametrized PDEs by proper orthogonal decom…☆30Updated last year
- ☆20Updated last year
- ☆12Updated this week
- ☆26Updated 9 months ago