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Chris Williams
Chris Williams
Professor of Machine Learning, University of Edinburgh
Verified email at inf.ed.ac.uk
Title
Cited by
Cited by
Year
Gaussian processes for machine learning
CE Rasmussen, CKI Williams
MIT Press, 2006
279652006
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
24685*2010
Gaussian processes in machine learning
CE Rasmussen, CKI Williams
Lecture notes in computer science 3176, 63-71, 2004
35372004
Using the Nyström method to speed up kernel machines
C Williams, M Seeger
Advances in neural information processing systems 13, 2000
27222000
Advances in neural information processing systems
H Lyu, N Sha, S Qin, M Yan, Y Xie, R Wang
Advances in neural information processing systems 32, 2019
2210*2019
GTM: The generative topographic mapping
CM Bishop, M Svensén, CKI Williams
Neural computation 10 (1), 215-234, 1998
18191998
Gaussian processes for regression
C Williams, C Rasmussen
Advances in neural information processing systems 8, 1995
15241995
Multi-task Gaussian process prediction
EV Bonilla, K Chai, C Williams
Advances in neural information processing systems 20, 2007
11992007
Bayesian classification with Gaussian processes
CKI Williams, D Barber
IEEE Transactions on pattern analysis and machine intelligence 20 (12), 1342 …, 1998
9491998
Prediction with Gaussian processes: From linear regression to linear prediction and beyond
CKI Williams
Learning in graphical models, 599-621, 1998
8941998
Gaussian process for machine learning
CE Rasmussen, CKI Williams
MIT press, 2006
860*2006
Gaussian processes for machine learning, vol. 2
CK Williams, CE Rasmussen
MA: MIT press Cambridge, 2006
5852006
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
5792003
Computing with infinite networks
C Williams
Advances in neural information processing systems 9, 1996
523*1996
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
4932006
Regression with input-dependent noise: A Gaussian process treatment
P Goldberg, C Williams, C Bishop
Advances in neural information processing systems 10, 1997
3831997
Timing of surgery following SARS‐CoV‐2 infection: an international prospective cohort study
COVIDSurg Collaborative, GlobalSurg Collaborative, D Nepogodiev, ...
Anaesthesia 76 (6), 748-758, 2021
3412021
The 2005 pascal visual object classes challenge
M Everingham, A Zisserman, CKI Williams, L Van Gool, M Allan, ...
Machine Learning Challenges. Evaluating Predictive Uncertainty, Visual …, 2006
3392006
A framework for the quantitative evaluation of disentangled representations
C Eastwood, CKI Williams
International Conference on Learning Representations, 2018
3082018
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
3041996
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