Chris Williams
Chris Williams
Professor of Machine Learning, University of Edinburgh
Verified email at
Cited by
Cited by
Gaussian processes for machine learning
CE Rasmussen, CKI Williams
MIT Press, 2006
Gaussian process for machine learning
CE Rasmussen, CKI Williams
MIT press, 2006
The PASCAL Visual Object Classes (VOC) challenge
M Everingham, L Van Gool, CKI Williams, J Winn, A Zisserman
Int J Computer Vision 88 (2), 303-338, 2010
Using the Nyström method to speed up kernel machines
C Williams, M Seeger
Proceedings of the 14th annual conference on neural information processing …, 2001
GTM: The generative topographic mapping
CM Bishop, M Svensén, CKI Williams
Neural computation 10 (1), 215-234, 1998
Gaussian processes for regression
CKI Williams, CE Rasmussen
MIT, 1996
Multi-task Gaussian process prediction
C Williams, EV Bonilla, KM Chai
Advances in neural information processing systems, 153-160, 2007
Bayesian classification with Gaussian processes
CKI Williams, D Barber
IEEE Transactions on Pattern Analysis and Machine Intelligence 20 (12), 1342 …, 1998
Prediction with Gaussian processes: From linear regression to linear prediction and beyond
CKI Williams
Learning in graphical models, 599-621, 1998
Fast forward selection to speed up sparse Gaussian process regression
MW Seeger, CKI Williams, ND Lawrence
International Workshop on Artificial Intelligence and Statistics, 254-261, 2003
Using machine learning to focus iterative optimization
F Agakov, E Bonilla, J Cavazos, B Franke, G Fursin, MFP O'Boyle, ...
International Symposium on Code Generation and Optimization (CGO'06), 11 pp.-305, 2006
Regression with input-dependent noise: A Gaussian process treatment
PW Goldberg, CKI Williams, CM Bishop
Advances in neural information processing systems 10, 493-499, 1997
The 2005 pascal visual object classes challenge
M Everingham, A Zisserman, CKI Williams, L Van Gool, M Allan, ...
Machine Learning Challenges Workshop, 117-176, 2005
Computing with infinite networks
CKI Williams
Advances in neural information processing systems, 295-301, 1997
Resin infusion under flexible tooling (RIFT): a review
C Williams, J Summerscales, S Grove
Composites Part A: Applied Science and Manufacturing 27 (7), 517-524, 1996
Dataset issues in object recognition
J Ponce, TL Berg, M Everingham, DA Forsyth, M Hebert, S Lazebnik, ...
Toward category-level object recognition, 29-48, 2006
Milepost gcc: Machine learning enabled self-tuning compiler
G Fursin, Y Kashnikov, AW Memon, Z Chamski, O Temam, M Namolaru, ...
International journal of parallel programming 39 (3), 296-327, 2011
The shape boltzmann machine: a strong model of object shape
SMA Eslami, N Heess, CKI Williams, J Winn
International Journal of Computer Vision 107 (2), 155-176, 2014
Using generative models for handwritten digit recognition
M Revow, CKI Williams, GE Hinton
IEEE transactions on pattern analysis and machine intelligence 18 (6), 592-606, 1996
Developments of the generative topographic mapping
CM Bishop, M Svensén, CKI Williams
Neurocomputing 21 (1-3), 203-224, 1998
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