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17 search results found

Learning-aided 3D mapping

Bayesian Optimization in JAX

Library for doing GPR (Gaussian Process Regression) in OCaml. Comes with a command line application.

Pytorch Minimal Gaussian Process ⭐ 38

A minimal implementation of Gaussian process regression in PyTorch

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.

Surfinbh ⭐ 17

Surrogate Final BH properties

SKBEL - Bayesian Evidential Learning framework built on top of scikit-learn.

Rgbd Correction ⭐ 15

Code and data accompanying our work on spatio-thermal depth correction of RGB-D sensors based on Gaussian Process Regression in real-time.

Differentiable Gaussian Process implementation for PyTorch

constrained/unconstrained multi-objective bayesian optimization package.

Multi Kernel Linear Mixed Models for Complex Phenotype Prediction

Gaussian_process_edge_trace ⭐ 9

Python module providing a framework to trace individual edges in an image using Gaussian process regression.

Interpolate grain boundary properties in a 5 degree-of-freedom sense via a novel distance metric.

Machinelearningalgos ⭐ 7

Personal reimplementation of some ML algorithms for learning purposes

Sparse Spectrum Gaussian Process Regression

Gaussianprocesses ⭐ 5

Modern C++ library handling gaussian processes

Modelling stellar activity signals with Gaussian process regression networks

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