kriging

Kriging Toolkit for Python

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

An extensible framework for high-performance geostatistics in Julia

Package with spatial analysis and spatial prediction tools

Fast, memory-efficient 3D spline interpolation and global kriging, via RBF (radial basis function) interpolation.

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.

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

Multifidelity Kriging, Efficient Global Optimization

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

Spatial interpolation python package

Generate stocastic Gaussian realization constrained to a coarse scale image.

Mandatory work for Introduction to Geostatistics course on University of Buenos Aires (UBA)

Gaussian process regression

Python tool for creating Kriging surrogate models

Software package for Gaussian Process (GP) modelling written in R language. The core functions are coded in C++ and based on the EIGEN library (through RcppEigen).