dopawei / DG-PINNsLinks
Data-guided physics-informed neural networks
☆15Updated last year
Alternatives and similar repositories for DG-PINNs
Users that are interested in DG-PINNs are comparing it to the libraries listed below
Sorting:
- Physcial Informed Extreme Learning Machine(PIELM) method to solve PDEs, such as Possion problem☆15Updated last year
- Dynamic weight strategy of physics-informed neural networks for the 2D Navier-Stokes equations☆14Updated 3 years ago
- Physics Informed Fourier Neural Operator☆24Updated last year
- Physics-informed convolutional-recurrent neural networks for solving spatiotemporal PDEs☆31Updated 3 years ago
- ☆21Updated 8 months ago
- Implementation of physics-informed PointNet (PIPN) for weakly-supervised learning of incompressible flows and thermal fields on irregular…☆13Updated 5 months ago
- DON-LSTM: Multi-Resolution Learning with DeepONets and Long-Short Term Memory Neural Networks☆11Updated 3 months ago
- Python codes for Locally Adaptive Activation Function (LAAF) used in deep neural networks. Please cite this work as "A D Jagtap, K Kawa…☆43Updated 2 years ago
- Separabale Physics-Informed DeepONets in JAX☆16Updated last year
- Multi-fidelity regression with neural networks☆16Updated last month
- Gradient-based adaptive sampling algorithms for self-supervising PINNs☆28Updated 2 years ago
- Simple demo on implementing data driven and physics informed Deep O Nets in pytorch☆19Updated last year
- Enhancing PINNs for Solving PDEs via Adaptive Collocation Point Movement and Adaptive Loss Weighting☆38Updated 2 years ago
- ☆13Updated last year
- Use of Turbulence Model (Spalart-Allmaras) with PINNs for mean flow reconstruction☆12Updated last year
- Solving a class of elliptic partial differential equations(PDEs) with multiple scales utilizing Fourier-based mixed physics informed neur…☆14Updated last year
- A collection of Jupyter notebooks providing tutorials on reduced order modeling techniques like DeepONet, FNO, DL-ROM, and POD-DL-ROM. Ea…☆27Updated 10 months ago
- Official Code for ICML 2024 paper "TENG: Time-Evolving Natural Gradient for Solving PDEs With Deep Neural Nets Toward Machine Precision"☆14Updated last year
- implementation of physics-informed variational auto-encoder☆20Updated 2 years ago
- Pytorch implementation of Bayesian physics-informed neural networks☆66Updated 4 years ago
- This repository contains the code and models for our paper "Investigating and Mitigating Failure Modes in Physics-informed Neural Network…☆19Updated 2 years ago
- ☆13Updated 2 years ago
- PECANNs: Physics and Equality Constrained Artificial Neural Networks☆24Updated 2 years ago
- ☆12Updated last week
- Implementation of Physics-Informed PointNet (PIPN) for weakly-supervised learning of 2D linear elasticity (plane stress) on multiple sets…☆12Updated last year
- Data preprocess method on Physics-informed neural networks☆24Updated 9 months ago
- ☆40Updated 2 years ago
- Research/development of physics-informed neural networks for dynamic systems☆32Updated last year
- A Backward Compatible -- Physics Informed Neural Network for Allen Cahn and Cahn Hilliard Equations☆35Updated 3 years ago
- PINN Implementation for IJCAI paper, "Physics-Informed Neural Networks: Minimizing Residual Loss with Wide Networks and Effective Activat…☆20Updated last year