An introduction to Gaussian processes applied to Bayesian regression

KadiPhotoMiroir

Kadi Bouatouch

University of Rennes, France

Abstract

The talk will address the Gaussian Process Theory and its application to  Global Illumination, rendering, regression, etc. Regression can be useful in many applications. For example it allows to perform a precise regression for a BRDF or an environment map for which the  sampled data (incident radiance, incident-reflected radiances) are not the most significant. Note that the Gaussian Process theory can be applied to different research fields such as crowd simulation, computer vision, etc.

Short Bio 

Kadi Bouatouch is an electronics and automatic systems engineer (ENSEM 1974, France). He was awarded a PhD in 1977 (University of Nancy 1, France) and a higher doctorate in computer science in the field of computer graphics in 1989 (University of Rennes 1, France). He is working on global illumination, lighting simulation for complex environments, GPU based rendering and computer vision. Currently, he is Emeritus Professor at the University of Rennes 1 (France) and researcher at IRISA Rennes (Institut de Recherche en Informatique et Systèmes Aléatoires). He was the head of the FRVSense team within IRISA until September 2017. He is member of Eurographics and was member of ACM and IEEE.  He was/are  member of the program committee of several conferences and workshops and referee for several Computer Graphics journals such as: The Visual Computer, ACM Trans. On Graphics, IEEE Computer Graphics and Applications, IEEE  Trans. On Visualization and Computer Graphics, IEEE Trans. On image processing, etc. He has also acted as a referee for many conferences and workshops. He served as a chair/committee member/reporter for several PhD theses or higher doctorates in France and abroad (USA, UK, Belgium, Cyprus, The Netherlands, Spain, etc.). He was associate editor for the Visual Computer Journal and is now General Co-Chair of the VISIGRAPP Conference.