evanchodora / krigingLinks
Python tool for creating Kriging surrogate models
☆18Updated 6 years ago
Alternatives and similar repositories for kriging
Users that are interested in kriging are comparing it to the libraries listed below
Sorting:
- In this repository I publish the python code, that was part of my master thesis. The thesis can be found here, however its in German thou…☆28Updated 5 years ago
- Python code to calculate proper orthogonal decomposition modes (aka principal components), which are then used to generate reduced order …☆35Updated 9 years ago
- Proper Orthogonal Decomposition - Radial Basis Function (POD-RBF) Network☆66Updated last year
- A MATLAB implementation of the co-kriging process using the DACE toolbox☆37Updated 8 years ago
- I am doing a surrogate optimization of a transonic airfoil. I am using an artificial neural network as my surrogate model to approximate …☆8Updated 4 years ago
- Python tools for non-intrusive reduced order modeling☆19Updated 2 months ago
- The STK is a (not so) Small Toolbox for Kriging. Its primary focus is on the interpolation/regression technique known as kriging, which i…☆41Updated 7 months ago
- Non-intrusive reduced order models using proper orthogonal decomposition (POD) and radial basis function (RBF) interpolation for shallow …☆18Updated 4 years ago
- Kriging for Analysis, Design optimization, And expLoration (KADAL)☆19Updated 3 years ago
- A modular code for teaching Surrogate Modeling-Based Optimization☆33Updated 5 years ago
- Deep Learning for Reduced Order Modelling☆100Updated 3 years ago
- This repository contains codes related to our work on physics-guided machine learning.☆15Updated 3 years ago
- Examplary code for NN, MFNN, DynNet, PINNs and CNN☆49Updated 3 years ago
- Multifidelity Kriging, Efficient Global Optimization☆18Updated 6 years ago
- ☆63Updated 5 years ago
- ☆39Updated 2 years ago
- Uncertainty Quantification in the POD-NN framework☆22Updated 4 years ago
- Tensoflow 2 implementation of physics informed deep learning.☆27Updated 4 years ago
- PINNs for 2D Incompressible Navier-Stokes Equation☆47Updated last year
- This is the source code for our paper "Towards high-accuracy deep learning inference of compressible turbulent flows over aerofoils"☆29Updated last year
- the proper orthogonal decomposition(POD) and dynamic mode decomposition(DMD) methods☆17Updated 5 years ago
- Source code for POD-DL-ROM: enhancing deep learning-based reduced order models for nonlinear parametrized PDEs by proper orthogonal decom…☆30Updated last year
- Multi-fidelity reduced-order surrogate modeling☆23Updated last month
- Deep Learning of Vortex Induced Vibrations☆95Updated 5 years ago
- multi-fidelity neural network☆18Updated last year
- A convolutional neural network for drag prediction in laminar flows☆14Updated 4 years ago
- ☆37Updated last year
- Surrogate Modeling for Fluid Flows Based on Physics-Constrained Label-Free Deep Learning☆88Updated last year
- Multi-fidelity modeling using Gaussian processes and nonlinear auto-regressive schemes.☆64Updated 8 years ago
- Examples implementing physics-informed neural networks (PINN) in Pytorch☆66Updated 3 years ago