DENG-MIT / Stiff-PINNLinks
Stiff-PINN: Physics-Informed Neural Network for Stiff Chemical Kinetics
☆66Updated 3 years ago
Alternatives and similar repositories for Stiff-PINN
Users that are interested in Stiff-PINN are comparing it to the libraries listed below
Sorting:
- Multifidelity deep neural operators for efficient learning of partial differential equations with application to fast inverse design of n…☆37Updated 2 years ago
- GCA-ROM is a library which implements graph convolutional autoencoder architecture as a nonlinear model order reduction strategy.☆36Updated last month
- POD-PINN code and manuscript☆56Updated last year
- In this repository, you will find the different python scripts to train the available models on the AirfRANS dataset proposed at the Neur…☆57Updated 11 months ago
- ☆54Updated 3 years ago
- Sparse Physics-based and Interpretable Neural Networks☆52Updated 4 years ago
- Code for the paper "Thermodynamics-informed graph neural networks" published in IEEE Transactions on Artificial Intelligence (TAI).☆105Updated last year
- Multi-fidelity reduced-order surrogate modeling☆28Updated 6 months ago
- ☆118Updated 6 years ago
- ☆24Updated 5 years ago
- Dimensionless learning☆41Updated this week
- Source code for the paper "Data-driven reduced-order models via regularised Operator Inference for a single-injector combustion process" …☆33Updated 3 years ago
- XPINN code written in TensorFlow 2☆28Updated 2 years ago
- Physics-Constrained Bayesian Neural Network for Fluid Flow Reconstruction with Sparse and Noisy Data☆50Updated 5 years ago
- A Backward Compatible -- Physics Informed Neural Network for Allen Cahn and Cahn Hilliard Equations☆36Updated 3 years ago
- PhyGeoNet: Physics-Informed Geometry-Adaptive Convolutional Neural Networks for Solving Parametric PDEs on Irregular Domain☆90Updated 4 years ago
- Reduced-Order Modeling of Fluid Flows with Transformers☆24Updated 2 years ago
- Tensoflow 2 implementation of physics informed deep learning.☆27Updated 5 years ago
- Competitive Physics Informed Networks☆32Updated last year
- Generative Adversarial Networks are used to super resolve turbulent flow fields from low resolution (RANS/LES) fields to high resolution …☆23Updated 4 years ago
- Sample codes of CNN-SINDy based reduced-order modeling for fluid flows by Fukami et al., JFM 2021.☆27Updated 4 years ago
- Theory-guided physics-informed neural networks for boundary layer problems with singular perturbation☆20Updated 3 years ago
- Source code of 'Deep transfer operator learning for partial differential equations under conditional shift'.☆75Updated 2 years ago
- Discontinuity Computing Using Physics-Informed Neural Network☆26Updated last year
- A sequential DeepONet model implementation that uses a recurrent neural network (GRU and LSTM) in the branch and a feed-forward neural ne…☆18Updated last year
- 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
- Physics-constrained auto-regressive convolutional neural networks for dynamical PDEs☆93Updated 3 years ago
- This repository contains the files used in the paper " Reduced-order Model for Fluid Flows via Neural Ordinary Differential Equations"☆19Updated 2 years ago
- Data-driven Reynolds stress modeling with physics-informed machine learning☆95Updated 6 years ago
- We propose a conservative physics-informed neural network (cPINN) on decompose domains for nonlinear conservation laws. The conservation …☆74Updated 2 years ago