Christopher K.I. Williams Computer sciences – Artificial Intelligence (expert systems - machine learning - robotics)
Christopher Williams is interested in a wide range of theoretical and practical issues in machine learning, statistical pattern recognition, probabilistic graphical models and computer vision. The main foci of his current research are prediction with Gaussian processes and image interpretation.
Winton Capital Research Prize
Overcoming Occlusion with Inverse Graphics. Pol Moreno, Christopher K.I. Williams, Charlie Nash and Pushmeet Kohli. Computer Vision-ECCV 2016 Workshops Proceedings Part III, eds. H. Gang and H. Jegou, Springer LNCS 9915 pp 170-185, 2016.
The PASCAL Visual Object Classes Challenge - a Retrospective. Mark Everingham, S. M. Ali Eslami, Luc Van Gool, Christopher K. I. Williams, John Winn, Andrew Zisserman. International Journal of Computer Vision 111(1), pp 98-136, 2015.
C. E. Rasmussen and C. K. I. Williams, Gaussian Processes for Machine Learning, MIT Press, 2006
Senior Fellow Learning in Machines & Brains
The University of EdinburghSchool of Informatics
PhD University of Toronto
MSc University of Toronto
BA (Physics and Theoretical Physics Class I) Cambridge University
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