maziarraissi / DeepLearningTutorial
Tutorial on a number of topics in Deep Learning
☆35Updated 5 years ago
Alternatives and similar repositories for DeepLearningTutorial:
Users that are interested in DeepLearningTutorial are comparing it to the libraries listed below
- Machine learning of linear differential equations using Gaussian processes☆24Updated 6 years ago
- Deep Learning of Vortex Induced Vibrations☆93Updated 5 years ago
- Deep Learning of Turbulent Scalar Mixing☆17Updated 5 years ago
- Numerical Gaussian Processes for Time-dependent and Non-linear Partial Differential Equations☆67Updated 4 years ago
- Physics-Informed Neural Networks for solving PDEs (bachelor project)☆10Updated 2 years ago
- Sample codes of CNN-SINDy based reduced-order modeling for fluid flows by Fukami et al., JFM 2021.☆25Updated 3 years ago
- XPINN code written in TensorFlow 2☆27Updated 2 years ago
- POD-PINN code and manuscript☆48Updated 4 months 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…☆30Updated 4 years ago
- Python code to calculate proper orthogonal decomposition modes (aka principal components), which are then used to generate reduced order …☆34Updated 9 years ago
- Finite Volume PINNs for Hyperbolic Conservation Laws & Compressible Flow☆18Updated 2 years ago
- TensorFlow 2.0 implementation of Yibo Yang, Paris Perdikaris’s adversarial Uncertainty Quantification in Physics Informed Neural Networks…☆19Updated 2 years ago
- PhyGeoNet: Physics-Informed Geometry-Adaptive Convolutional Neural Networks for Solving Parametric PDEs on Irregular Domain☆84Updated 4 years ago
- Physics-informed neural networks for highly compressible flows 🧠🌊☆25Updated last year
- This repository contains the simple source codes of "Convolutional neural network and long short-term memory based reduced order surrogat…☆13Updated 4 years ago
- Surrogate Modeling for Fluid Flows Based on Physics-Constrained Label-Free Deep Learning☆84Updated last year
- Data-driven Reynolds stress modeling with physics-informed machine learning☆92Updated 6 years ago
- Theory-guided physics-informed neural networks for boundary layer problems with singular perturbation☆16Updated 2 years ago
- A library of tools for computing variants of Dynamic Mode Decomposition☆46Updated 7 years ago
- PINNs for 2D Incompressible Navier-Stokes Equation☆43Updated 10 months ago
- This code implements the Tensor Basis Neural Network (TBNN) as described in Ling et al. (Journal of Fluid Mechanics, 2016).☆40Updated 7 years ago
- Discontinuity Computing Using Physics-Informed Neural Network☆23Updated 11 months ago
- Source code for the paper "Data-driven reduced-order models via regularised Operator Inference for a single-injector combustion process" …☆30Updated 2 years ago
- Proper Orthogonal Decomposition - Radial Basis Function (POD-RBF) Network☆65Updated last year
- SIMPLE Algorithm for Driven Cavity problem on collocated grid using Python.☆22Updated 4 years ago
- ☆62Updated 5 years ago
- Source code for POD-DL-ROM: enhancing deep learning-based reduced order models for nonlinear parametrized PDEs by proper orthogonal decom…☆29Updated 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
- Soving heat transfer problems using PINN with tf2.0☆20Updated 3 years ago
- A Deep Learning based Approach to Reduced Order Modeling for Turbulent Flow Control using LSTM Neural Networks. arXiv:1804.09269☆41Updated 6 years ago