Chris Williams

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Andrew ZissermanUniversity of OxfordVerified email at robots.ox.ac.uk
Luc Van Goolprofessor computer vision ETHZ, KULeuven, INSAIT Sofia University,Toyota Lab TRACEVerified email at insait.ai
Carl Edward RasmussenProfessor of Machine Learning, University of CambridgeVerified email at cam.ac.uk
S. M. Ali EslamiGoogle DeepMindVerified email at google.com
Christopher M. BishopTechnical Fellow, Microsoft Research, Cambridge, U.K.Verified email at microsoft.com
Edwin V. BonillaPrincipal Research Scientist, CSIRO's Data61Verified email at data61.csiro.au
Geoffrey HintonEmeritus Prof. Computer Science, University of TorontoVerified email at cs.toronto.edu
Matthias SeegerPrincipal Applied Scientist, Amazon, BerlinVerified email at amazon.de
John Shawe-TaylorUCLVerified email at cs.ucl.ac.uk
Richard ZemelProfessor of Computer Science, University of TorontoVerified email at cs.toronto.edu
John QuinnGoogle Research, Sunbird AI, Makerere UniversityVerified email at cit.ac.ug
David BarberDepartment of Computer Science, University College LondonVerified email at ucl.ac.uk
Michael MozerGoogle DeepMind; University of ColoradoVerified email at colorado.edu
Jyri J. KivinenUniversity of LaplandVerified email at ulapland.fi
Neil D. LawrenceUniversity of CambridgeVerified email at cl.cam.ac.uk
Marc ToussaintProfessor of Computer Science, TU Berlin, GermanyVerified email at tu-berlin.de
Miguel Á. Carreira-PerpiñánProfessor of Computer Science, University of California, MercedVerified email at ucmerced.edu
Ian T. NabneyProfessor and Head of SCEEM, University of BristolVerified email at bristol.ac.uk
Joaquin Quiñonero CandelaOpenAIVerified email at openai.com
Volker TrespLudwig-Maximilians-Universität München (LMU Munich)Verified email at dbs.ifi.lmu.de

Chris Williams

Professor of Machine Learning, University of Edinburgh

Verified email at inf.ed.ac.uk

Machine learning pattern recognition computer vision


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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	22611	2010
The Pascal Visual Object Classes Challenge: A Retrospective M Everingham, SMA Eslami, L Van Gool, CKI Williams, J Winn, ... International journal of computer vision 111, 98-136, 2015	11017	2015
Gaussian processes for machine learning CE Rasmussen, CKI Williams MIT Press, 2006	4697*	2006
Using the Nyström method to speed up kernel machines C Williams, M Seeger Advances in neural information processing systems 13, 2000	3037	2000
GTM: The generative topographic mapping CM Bishop, M Svensén, CKI Williams Neural computation 10 (1), 215-234, 1998	1909	1998
Gaussian processes for regression C Williams, C Rasmussen Advances in neural information processing systems 8, 1995	1850	1995
Multi-task Gaussian process prediction EV Bonilla, K Chai, C Williams Advances in neural information processing systems 20, 2007	1438	2007
Bayesian classification with Gaussian processes CKI Williams, D Barber IEEE Transactions on pattern analysis and machine intelligence 20 (12), 1342 …, 1998	1042	1998
Prediction with Gaussian processes: From linear regression to linear prediction and beyond CKI Williams Learning in graphical models, 599-621, 1998	973	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	652	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	528	2006
A framework for the quantitative evaluation of disentangled representations C Eastwood, CKI Williams 6th International Conference on Learning Representations, 2018	467	2018
Regression with input-dependent noise: A Gaussian process treatment P Goldberg, C Williams, C Bishop Advances in neural information processing systems 10, 1997	452	1997
Computing with infinite networks C Williams Advances in neural information processing systems 9, 1996	446	1996
On a connection between kernel PCA and metric multidimensional scaling C Williams Advances in neural information processing systems 13, 2000	344	2000
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, 296-327, 2011	328	2011
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	317	2006
Harmonising chorales by probabilistic inference M Allan, C Williams Advances in neural information processing systems 17, 2004	270	2004
Developments of the generative topographic mapping CM Bishop, M Svensén, CKI Williams Neurocomputing 21 (1-3), 203-224, 1998	269	1998
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	269	1996

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