Duke-MG-Lab / Allen-Cahn-FNOLinks
Fourier Neural Operators to solve for Allen Cahn PDE equations
☆18Updated 3 years ago
Alternatives and similar repositories for Allen-Cahn-FNO
Users that are interested in Allen-Cahn-FNO are comparing it to the libraries listed below
Sorting:
- Discontinuity Computing Using Physics-Informed Neural Network☆24Updated last year
- Deep finite volume method☆21Updated 11 months ago
- Coupled-Automatic-Numerical differentiation scheme for physics-informed neural network (can-PINN)☆28Updated last year
- Reduced-Order Modeling of Fluid Flows with Transformers☆24Updated 2 years ago
- Sparse Physics-based and Interpretable Neural Networks☆50Updated 3 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…☆40Updated 2 years ago
- A Backward Compatible -- Physics Informed Neural Network for Allen Cahn and Cahn Hilliard Equations☆31Updated 3 years ago
- POD-PINN code and manuscript☆51Updated 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
- ☆53Updated 2 years ago
- Accelerating Physics Informed Neural Networks (PINNs) using Meshless Discretizations☆27Updated 2 years ago
- MIONet: Learning multiple-input operators via tensor product☆34Updated 2 years ago
- XPINN code written in TensorFlow 2☆27Updated 2 years ago
- ☆29Updated 2 years ago
- ☆50Updated 5 months ago
- ☆26Updated 10 months ago
- ☆41Updated 2 years ago
- DeepONet extrapolation☆27Updated 2 years ago
- Multifidelity DeepONet☆33Updated last year
- hp-VPINNs: variational physics-informed neural network with domain decomposition is a general framework to solve differential equations☆78Updated 2 years ago
- Gradient-based adaptive sampling algorithms for self-supervising PINNs☆26Updated 2 years ago
- Code for 'Physics-Informed Neural Networks for Shell Structures'☆38Updated 9 months ago
- ☆14Updated 2 years ago
- Learning two-phase microstructure evolution using neural operators and autoencoder architectures☆23Updated 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 4 months ago
- KTH-FlowAI / beta-Variational-autoencoders-and-transformers-for-reduced-order-modelling-of-fluid-flows☆31Updated last month
- ☆32Updated last year
- ☆11Updated 3 years ago
- Fourier Neural Operator☆12Updated 2 years ago
- Code for "Beyond Regular Grids: Fourier-Based Neural Operators on Arbitrary Domains"☆19Updated last year