Christopher K. I. Williams

LMB_ChristopherWilliams

Appointment

  • Associate Fellow
  • Learning in Machines & Brains

Institution

  • University of Edinburgh
School of Informatics

Country

  • United Kingdom

Education

PhD, University of Toronto
MSc, University of Toronto
BA (Physics and Theoretical Physics Class I), Cambridge University

About

Christopher Williams is a computer scientist who works in artificial intelligence (expert systems, machine learning, robotics).

He is interested in a wide range of theoretical and practical issues in machine learning, statistical pattern recognition, probabilistic graphical models and computer vision. His current research focuses on prediction with Gaussian processes and image interpretation.

Awards

Winton Capital Research Prize

Relevant Publications

Moreno, Pol. “Overcoming Occlusion with Inverse Graphics.” In Computer Vision-ECCV 2016 Workshops Proceedings, Part III, edited by H. Gang and H. Jegou, 170–185.

Everingham, M. et al. “The PASCAL Visual Object Classes Challenge - a Retrospective.” International Journal of Computer Vision 111, no. 1 (2015): 98–136.

Rasmussen, C.E., and C.K.I. Williams. Gaussian Processes for Machine Learning. Cambridge, MA: MIT Press, 2006.

Connect

Website