elhamwasei / PINNsLinks
Physics-Informed Neural Networks for solving PDEs (bachelor project)
☆10Updated 2 years ago
Alternatives and similar repositories for PINNs
Users that are interested in PINNs are comparing it to the libraries listed below
Sorting:
- TensorFlow 2.0 implementation of Yibo Yang, Paris Perdikaris’s adversarial Uncertainty Quantification in Physics Informed Neural Networks…☆20Updated 2 years ago
- ☆12Updated 2 years ago
- This repository contains the simple source codes of "Machine-learning-based reduced-order modeling for unsteady flows around bluff bodies…☆16Updated 4 years ago
- POD-PINN code and manuscript☆54Updated 11 months ago
- XPINN code written in TensorFlow 2☆28Updated 2 years ago
- Sample codes of CNN-SINDy based reduced-order modeling for fluid flows by Fukami et al., JFM 2021.☆26Updated 4 years ago
- ☆21Updated 5 years ago
- Finite Volume PINNs for Hyperbolic Conservation Laws & Compressible Flow☆19Updated 2 years ago
- Yet another PINN implementation☆20Updated last year
- Multifidelity deep neural operators for efficient learning of partial differential equations with application to fast inverse design of n…☆35Updated 2 years ago
- This repository contains the files used in the paper " Reduced-order Model for Fluid Flows via Neural Ordinary Differential Equations"☆18Updated 2 years ago
- Generative Adversarial Networks are used to super resolve turbulent flow fields from low resolution (RANS/LES) fields to high resolution …☆23Updated 4 years ago
- Data-driven Identification of 2D Partial Differential Equations using Extracted Physical Features☆12Updated 4 years ago
- ☆12Updated this week
- Discontinuity Computing Using Physics-Informed Neural Network☆26Updated last year
- Physics-informed neural networks for highly compressible flows 🧠🌊☆27Updated last year
- ☆26Updated 7 years ago
- Source code for deep learning-based reduced order models in cardiac electrophysiology. Available on doi.org/10.1371/journal.pone.0239416.☆15Updated 2 years ago
- Theory-guided physics-informed neural networks for boundary layer problems with singular perturbation☆20Updated 2 years ago
- This repository contains the simple source codes of "Convolutional neural network and long short-term memory based reduced order surrogat…☆15Updated 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…☆25Updated 9 months ago
- Source code for deep learning-based reduced order models for nonlinear time-dependent parametrized PDEs. Available on doi.org/10.1007/s10…☆25Updated 2 years ago
- Sparse Identification of Nonlinear Dynamics for Boundary Value Problems☆13Updated 4 years ago
- A Backward Compatible -- Physics Informed Neural Network for Allen Cahn and Cahn Hilliard Equations☆34Updated 3 years ago
- POD and DMD decomposition of data from fluid dynamics. This work has been produced during my internship at the von Karman Institute for F…☆32Updated 5 years ago
- Multi-fidelity reduced-order surrogate modeling☆25Updated 4 months ago
- Physics-Constrained Bayesian Neural Network for Fluid Flow Reconstruction with Sparse and Noisy Data☆49Updated 5 years ago
- PINNs-MPF is a comprehensive framework designed for simulating interface dynamics using Physics-Informed Neural Networks (PINNs). Leverag…☆17Updated 6 months ago
- Deep Learning based method to try and learn the problem of inverse Navier Stokes and model the flow for an oscillating airfoil.☆23Updated 5 years ago
- Physics-Informed Super-Resolution☆10Updated 2 years ago