Network on Gaussian Processes


In essence, the concept of “Gaussian Processes” (GP) exists for many years, but during the last few years they pop up in different disciplines, often presented in a new toolkit.

In December 2019 we launched an interdisciplinary interest group around the possibilities and the challenges of GP. The objective was (and still is) the organic expansion of a platform for discussions and sharing of ideas on theoretical contributions and practical applications, creating a fertile soil for future cooperation and project proposals.

You should care about this topic as soon as you get involved in topics like probabilistic numerics, interpolation and optimization in uncertain environments, explainable machine learning, design of sample measurements and pseudo-inputs, etc...


Modelling the Human Anatomy Using Gaussian Processes

Online seminar by Marcel Lüthi (University of Basel)

Date: 09/06/2021

An introduction to Bayesian optimization

Online seminar by Ivo Couckuyt (Ghent University)

Date: 23/02/2021

Fleet-Wide Policy Iteration using Gaussian Processes

Lunch seminar by Timothy Verstraeten (Vrije Universiteit Brussel)

Date: 26/02/2020

Exploiting Structure in Bayesian Optimization using Multi-Fidelity Probabilistic Models

Pilot lunch by Boris Bogaerts (UAntwerp) and Ivan De Boi (UAntwerp)

Date: 12/12/2019


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De Boi, I.; Ribbens, B.; Jorissen, P.; Penne, R. Feasibility of Kd-Trees in Gaussian Process Regression to Partition Test Points in High Resolution Input Space. Algorithms2020, 13, 327.

Verstraeten, T., Libin, P. & Nowé, A. (2020), Fleet Control using Coregionalized Gaussian Process Policy Iteration. In: Proceedings of the 24th European Conference on Artificial Intelligence (ECAI 2020). IOS Press, pp. 1571-1578, European Conference on Artificial Intelligence (ECAI 2020), Santiago De Compostela, Spain, 29/08/20.