kriging

Kriging Toolkit for Python

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

Fast radial basis function interpolation and kriging 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

kriging library for performance and wide language support

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.

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. :/

The repo is the official implementation for the paper: MoGERNN: An Inductive Traffic Predictor for Unobserved Locations.

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

Python tool for creating Kriging surrogate models

Multifidelity Kriging, Efficient Global Optimization

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

Kriging estimators for the GeoStats.jl framework

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

Generate stocastic Gaussian realization constrained to a coarse scale image.

A Rust implementation of the core algorithms of GSTools.

"Space-Time Interpolation and Forecasting" - Predicting spatio-temporally distributed variables via space-time regression kriging using numpy and numba.