Blue-Giant / PIELM_NumpyLinks
Physcial Informed Extreme Learning Machine(PIELM) method to solve PDEs, such as Possion problem
☆17Updated last year
Alternatives and similar repositories for PIELM_Numpy
Users that are interested in PIELM_Numpy are comparing it to the libraries listed below
Sorting:
- Implementations of the "randomize-then-optimize" approach for sampling Bayesian Physics-informed Neural Network posteriors☆13Updated 9 months ago
- 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
- Solving a class of elliptic partial differential equations(PDEs) with multiple scales utilizing Fourier-based mixed physics informed neur…☆15Updated last year
- SK-PINN: Accelerated physics-informed deep learning by smoothing kernel gradients☆23Updated 9 months ago
- Data preprocess method on Physics-informed neural networks☆26Updated 11 months ago
- ☆18Updated last month
- Physics-informed deep learning for structural dynamics under moving load☆19Updated last year
- Dynamic weight strategy of physics-informed neural networks for the 2D Navier-Stokes equations☆14Updated 3 years ago
- ☆23Updated last year
- ☆12Updated last year
- 🏔️ PINNACLE: PINN Adaptive ColLocation and Experimental points selection☆27Updated last year
- ☆17Updated last year
- ☆27Updated last year
- Implementation of physics-informed PointNet (PIPN) for weakly-supervised learning of incompressible flows and thermal fields on irregular…☆13Updated 7 months ago
- Deep finite volume method☆21Updated last year
- Gradient-based adaptive sampling algorithms for self-supervising PINNs☆28Updated 2 years ago
- MATLAB codes for the RPIM-NNS☆14Updated last year
- Variational Physic-informed Neural Operator (VINO) for Learning Partial Differential Equations☆29Updated 4 months ago
- Enhancing PINNs for Solving PDEs via Adaptive Collocation Point Movement and Adaptive Loss Weighting☆39Updated 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
- ☆13Updated 3 years ago
- Official Code for ICML 2024 paper "TENG: Time-Evolving Natural Gradient for Solving PDEs With Deep Neural Nets Toward Machine Precision"☆18Updated last year
- Super-resolution and denoising of fluid flow using physics-informed convolutional neural networks without high-resolution labels -- param…☆23Updated 4 years ago
- Data-guided physics-informed neural networks☆16Updated last year
- Neural integration for constitutive equations☆12Updated 2 years ago
- DON-LSTM: Multi-Resolution Learning with DeepONets and Long-Short Term Memory Neural Networks☆11Updated 4 months ago
- Accompanyig code for "Training Physics-Informed Neural Networks: one learning to rule them all?"☆13Updated 3 years ago
- Official Implementation of "AIVT: Inference of turbulent thermal convection from measured 3D velocity data by physics-informed Kolmogorov…☆16Updated 3 months ago
- This is the official implementation of "Deep Fuzzy Physics-Informed Neural Networks for Forward and Inverse PDE Problems" (Neural Network…☆27Updated 3 months ago
- Boosting the training of physics informed neural networks with transfer learning☆27Updated 4 years ago