Kriging Toolkit for Python

GSTools - A geostatistical toolbox: random fields, variogram estimation, covariance models, kriging and much more

Fast radial basis function interpolation for large scale data

Kriging | Poisson Kriging | Variogram Analysis

This repository contains the source code for “Thompson sampling efficient multiobjective optimization” (TSEMO).

Geostatistics in Python

GammaRay: a graphical interface to GSLib and other geomodeling algorithms. *NEW* in May, 6th: Drift analysis.

The STK is a (not so) Small Toolbox for Kriging. Its primary focus is on the interpolation/regression technique known as kriging, which is very closely related to Splines and Radial Basis Functions, and can be interpreted as a non-parametric Bayesian method using a Gaussian Process (GP) prior.

kriging library for performance and wide language support

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 though, sry. :/

Python tool for creating Kriging surrogate models

Kriging estimators for the GeoStats.jl framework

Multifidelity Kriging, Efficient Global Optimization

Mapping of groundwater level for realistic flow flowpaths using semi-automated kriging.

Implementation of image reparation and inpainting using Gaussian Conditional Simulation. Created as part of Unity Technologies research.

Generate stocastic Gaussian realization constrained to a coarse scale image.

Spatial interpolation python package

GMPE-estimation implements a one-stage estimation algorithm to estimate ground-motion prediction equations (GMPE) with spatial correlation. It also quantifies the uncertainty of spatial correlation and intensity measure predictions.

Gaussian process regression

Evaluating model calibration methods for sensitivity analysis, uncertainty analysis, optimisation, and Bayesian inference