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

Geostatistics in Python

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

GammaRay: a graphical interface to GSLib and other geomodeling algorithms. *NEW* in Apr, 11th: Contact 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. :/

Kriging estimators for the GeoStats.jl framework

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

Multifidelity Kriging, Efficient Global Optimization

Python tool for creating Kriging surrogate models

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

Spatial interpolation python package

Gaussian process regression

Generate stocastic Gaussian realization constrained to a coarse scale image.

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.

A Rust implementation of the core algorithms of GSTools.