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…☆29Updated 6 years ago
- Python code to calculate proper orthogonal decomposition modes (aka principal components), which are then used to generate reduced order …☆38Updated 10 years ago
- Deep Learning of Vortex Induced Vibrations☆99Updated 5 years ago
- Deep Learning for Reduced Order Modelling☆101Updated 4 years ago
- A Tensorflow re-implementation of the paper Convolutional Neural Networks for Steady Flow Approximation☆167Updated 7 years ago
- ☆63Updated 6 years ago
- ☆74Updated last year
- Bayesian deep convolutional encoder-decoder networks for surrogate modeling and uncertainty quantification☆107Updated 5 years ago
- Proper Orthogonal Decomposition - Radial Basis Function (POD-RBF) Network☆69Updated 2 years ago
- Surrogate Modeling for Fluid Flows Based on Physics-Constrained Label-Free Deep Learning☆93Updated 2 years ago
- ☆70Updated last year
- ☆131Updated 3 years ago
- A Matlab toolbox for stochastic response analysis by DR-PDEE/GE-GDEE☆29Updated 2 years ago
- PhyGeoNet: Physics-Informed Geometry-Adaptive Convolutional Neural Networks for Solving Parametric PDEs on Irregular Domain☆88Updated 4 years ago
- A MATLAB implementation of the co-kriging process using the DACE toolbox☆40Updated 8 years ago
- Deep learning for Engineers - Physics Informed Deep Learning☆353Updated last year
- flowTorch - a Python library for analysis and reduced-order modeling of fluid flows☆161Updated 3 weeks ago
- Physics-Constrained Bayesian Neural Network for Fluid Flow Reconstruction with Sparse and Noisy Data☆49Updated 5 years ago
- We introduce an innovative physics-informed LSTM framework for metamodeling of nonlinear structural systems with scarce data.☆97Updated 2 years ago
- Python script for Linear, Non-Linear Convection, Burger’s & Poisson Equation in 1D & 2D, 1D Diffusion Equation using Standard Wall Functi…☆233Updated last year
- Source code for POD-DL-ROM: enhancing deep learning-based reduced order models for nonlinear parametrized PDEs by proper orthogonal decom…☆33Updated 2 years ago
- Deep Learning and Finite Element Method for Physical Systems Modeling☆51Updated 6 years ago
- Gradient-enhanced physics-informed neural networks for forward and inverse PDE problems☆103Updated 3 years ago
- A place to share problems solved with SciANN☆297Updated 2 years ago
- Examples implementing physics-informed neural networks (PINN) in Pytorch☆80Updated 4 years ago
- A Python package for spectral proper orthogonal decomposition (SPOD).☆114Updated 2 weeks 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
- Physics Informed Neural Network (PINN) for Burgers' equation.☆71Updated last year
- IDRLnet, a Python toolbox for modeling and solving problems through Physics-Informed Neural Network (PINN) systematically.☆243Updated last year
- Hidden physics models: Machine learning of nonlinear partial differential equations☆147Updated 5 years ago