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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

Relevant Publications

P. W. Goldberg et al, "Regression with input-dependent noise: A Gaussian process treatment," Advances in neural information processing systems, vol. 10, pp. 493-499, 1997.


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


BA (Physics and Theoretical Physics Class I) Cambridge University


United Kingdom

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