Abstract: Gaussian process regression (GPR) has experienced tremendous success in biophysical parameter retrieval in the past years. The GPR provides a full posterior predictive distribution so one ...

JuliaGPs is an organisation interested in making Gaussian process models work well in the Julia programming language. The packages in this ecosystem are targeted at people who want to use Gaussian ...

Python's scripting capabilities make it an ideal partner for OpenUSD, facilitating task automation and accelerating development processes. While OpenUSD is implemented primarily in C++, offering a ...

The control design is based on Gaussian process (GP) regression models that are learned from experiments without requiring a priori knowledge about the robot dynamics or the demonstration of ...

This repository contains a Python implementation of the Wasserstein Distance, Wasserstein Barycenter and Optimal Transport Map of Gaussian Processes. Based on the papers: Mallasto, Anton, and Aasa ...

This important study presents compelling observational data supporting a role for transcription and polysome accumulation in the separation of newly replicated bacterial chromosomes. The study is ...