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

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

Multifidelity Kriging, Efficient Global Optimization

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

A Rust implementation of the core algorithms of GSTools.