Blue-Giant / FMPINNLinks
Solving a class of elliptic partial differential equations(PDEs) with multiple scales utilizing Fourier-based mixed physics informed neural networks(dubbed FMPINN), the solver of FMPINN is configured as a multi-scale deep neural networks.
☆14Updated last year
Alternatives and similar repositories for FMPINN
Users that are interested in FMPINN are comparing it to the libraries listed below
Sorting:
- SK-PINN: Accelerated physics-informed deep learning by smoothing kernel gradients☆23Updated 9 months ago
- Data preprocess method on Physics-informed neural networks☆26Updated 10 months ago
- ☆17Updated 2 weeks ago
- ☆22Updated 8 months ago
- Physics Informed Fourier Neural Operator☆26Updated last year
- Solving High Frequency and Multi-Scale PDEs with Gaussian Processes (ICLR 2024)☆25Updated last year
- This project is divided in a two parts. In first study, Lame parameters are identified using tanh activation function. After that, six a…☆13Updated 3 years ago
- Implementations of the "randomize-then-optimize" approach for sampling Bayesian Physics-informed Neural Network posteriors☆13Updated 8 months ago
- Physics-informed deep learning for structural dynamics under moving load☆19Updated last year
- Gradient-based adaptive sampling algorithms for self-supervising PINNs☆28Updated 2 years ago
- Data-guided physics-informed neural networks☆15Updated last year
- Deep finite volume method☆21Updated last year
- Physics-informed deep super-resolution of spatiotemporal data☆49Updated 2 years ago
- ☆12Updated last year
- Enhancing PINNs for Solving PDEs via Adaptive Collocation Point Movement and Adaptive Loss Weighting☆38Updated 2 years ago
- A python implementation of Physics-informed Spline Learning for nonlinear dynamics discovery.☆27Updated 4 years ago
- Physcial Informed Extreme Learning Machine(PIELM) method to solve PDEs, such as Possion problem☆16Updated last year
- ☆24Updated 2 years ago
- The code for the paper Temperature field inversion of heat-source systems via physics-informed neural networks☆41Updated 3 years ago
- Physics-informed convolutional-recurrent neural networks for solving spatiotemporal PDEs☆31Updated 4 years ago
- Super-resolution and denoising of fluid flow using physics-informed convolutional neural networks without high-resolution labels -- param…☆23Updated 4 years ago
- A collection of Jupyter notebooks providing tutorials on reduced order modeling techniques like DeepONet, FNO, DL-ROM, and POD-DL-ROM. Ea…☆28Updated 11 months ago
- ☆21Updated 2 years ago
- DON-LSTM: Multi-Resolution Learning with DeepONets and Long-Short Term Memory Neural Networks☆11Updated 4 months ago
- Implementation of physics-informed PointNet (PIPN) for weakly-supervised learning of incompressible flows and thermal fields on irregular…☆13Updated 6 months ago
- This is the implementation of the RecFNO.☆25Updated 2 years ago
- Code of the publication "Physics informed neural networks for continuum micromechanics" published in https://doi.org/10.1016/j.cma.2022.1…☆19Updated 3 years ago
- MATLAB codes for the RPIM-NNS☆14Updated last year
- An implementation of Physics-Informed Neural Networks (PINNs) to solve various forward and inverse problems for the 1 dimensional wave eq…☆42Updated 3 years ago
- ☆26Updated 3 years ago