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...
Hybrid seminar by Søren Hauberg
(Technical University of Denmark)
Hybrid seminar by Stephen Roberts (Oxford University)
Lunch seminar on
Dynamic line scan thermography parameter design via Gaussian process emulation
by Simon Verspeek (UAntwerp)
Understanding the Significance, Processing and Analysis of Point Clouds
by Stuti Pathak (UAntwerp)
Bayesian Deep Learning with Physics-informed Gaussian Processes
by Thomas McDonald (University of Manchester)
Online seminar by Carl Henrik Ek (Cambridge University)
Online seminar by Inneke Van Nieuwenhuyse (UHasselt)
Date: 23/12/2021
Online seminar by Marcel Lüthi (University of Basel)
Date: 09/06/2021
Online seminar by Ivo Couckuyt (Ghent University)
Date: 23/02/2021
Lunch seminar by Timothy Verstraeten (Vrije Universiteit Brussel)
Date: 26/02/2020
Pilot lunch by Boris Bogaerts (UAntwerp) and Ivan De Boi (UAntwerp)
Date: 12/12/2019
Copyright © UAntwerp InViLab research group 2024