isds-neu / PeRCNN
Encoding physics to learn reaction-diffusion processes
☆96Updated last year
Alternatives and similar repositories for PeRCNN:
Users that are interested in PeRCNN are comparing it to the libraries listed below
- Source code of "Learning nonlinear operators in latent spaces for real-time predictions of complex dynamics in physical systems."☆58Updated 8 months ago
- Physics-encoded recurrent convolutional neural network☆46Updated 3 years ago
- Source code of 'Deep transfer operator learning for partial differential equations under conditional shift'.☆70Updated last year
- ☆120Updated 5 months ago
- ☆49Updated 3 months ago
- Physics-informed convolutional-recurrent neural networks for solving spatiotemporal PDEs☆147Updated 11 months ago
- ☆70Updated last year
- gPINN: Gradient-enhanced physics-informed neural networks☆88Updated 3 years ago
- ☆48Updated 4 months ago
- ☆160Updated last year
- DeepONet & FNO (with practical extensions)☆284Updated last year
- Original implementation of fast PINN optimization with RBA weights☆50Updated this week
- Official implementation of "PhyGNNet: Solving spatiotemporal PDEs with Physics-informed Graph Neural Network"☆42Updated last year
- Physics-informed learning of governing equations from scarce data☆140Updated last year
- PDE Preserved Neural Network☆46Updated 9 months ago
- About Code Release for "Solving High-Dimensional PDEs with Latent Spectral Models" (ICML 2023), https://arxiv.org/abs/2301.12664☆69Updated last week
- U-FNO - an enhanced Fourier neural operator-based deep-learning model for multiphase flow☆128Updated 7 months ago
- Physics-informed graph neural Galerkin networks: A unified framework for solving PDE-governed forward and inverse problems☆51Updated 3 years ago
- ☆72Updated 7 months ago
- Generative Pre-Trained Physics-Informed Neural Networks Implementation☆89Updated 2 months ago
- ☆133Updated 2 years ago
- ☆53Updated 2 years ago
- A large-scale benchmark for machine learning methods in fluid dynamics☆187Updated 4 months ago
- Physics-informed deep super-resolution of spatiotemporal data☆42Updated last year
- Non-adaptive and residual-based adaptive sampling for PINNs☆70Updated 2 years ago
- PINN (Physics-Informed Neural Networks) on Navier-Stokes Equations☆95Updated 2 years ago
- Physics Informed Fourier Neural Operator☆20Updated 4 months ago
- ☆47Updated last year
- Characterizing possible failure modes in physics-informed neural networks.☆132Updated 3 years ago
- when using, please cite "Bayesian Physics-Informed Neural Networks for real-world nonlinear dynamical systems", CMAME, https://doi.org/1…☆69Updated 2 years ago