Chris Williams

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Andrew ZissermanUniversity of OxfordDirección de correo verificada de robots.ox.ac.uk
Luc Van Goolprofessor computer vision INSAIT Sofia University, em. KU Leuven, em. ETHZ, Toyota Lab TRACEDirección de correo verificada de insait.ai
Carl Edward RasmussenProfessor of Machine Learning, University of CambridgeDirección de correo verificada de cam.ac.uk
S. M. Ali EslamiGoogle DeepMindDirección de correo verificada de google.com
Christopher M. BishopTechnical Fellow, Microsoft Research, Cambridge, U.K.Dirección de correo verificada de microsoft.com
Edwin V. BonillaPrincipal Research Scientist, CSIRO's Data61Dirección de correo verificada de data61.csiro.au
Geoffrey HintonEmeritus Prof. Computer Science, University of TorontoDirección de correo verificada de cs.toronto.edu
Matthias SeegerPrincipal Applied Scientist, Amazon, BerlinDirección de correo verificada de amazon.de
John Shawe-TaylorUCLDirección de correo verificada de cs.ucl.ac.uk
John QuinnGoogle Research, Sunbird AI, Makerere UniversityDirección de correo verificada de cit.ac.ug
Richard ZemelProfessor of Computer Science, University of TorontoDirección de correo verificada de cs.toronto.edu
David BarberDepartment of Computer Science, University College LondonDirección de correo verificada de ucl.ac.uk
Michael MozerGoogle DeepMind; University of ColoradoDirección de correo verificada de colorado.edu
Neil D. LawrenceUniversity of CambridgeDirección de correo verificada de cl.cam.ac.uk
Marc ToussaintProfessor of Computer Science, TU Berlin, GermanyDirección de correo verificada de tu-berlin.de
Miguel Á. Carreira-PerpiñánProfessor of Computer Science, University of California, MercedDirección de correo verificada de ucmerced.edu
Ian T. NabneyProfessor and Associate Dean, Faculty of Science and Engineering, University of BristolDirección de correo verificada de bristol.ac.uk
Joaquin Quiñonero CandelaOpenAIDirección de correo verificada de openai.com
Volker TrespLudwig-Maximilians-Universität München (LMU Munich)Dirección de correo verificada de dbs.ifi.lmu.de
Sethu VijayakumarProfessor of Robotics, University of Edinburgh; Programme Director at The Alan Turing Institute, UKDirección de correo verificada de ed.ac.uk

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Chris Williams

Professor of Machine Learning, University of Edinburgh

Dirección de correo verificada de inf.ed.ac.uk

Machine learning pattern recognition computer vision


Título Ordenar por citas Ordenar por año Ordenar por título	Citado por Citado por	Año
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	23975	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	11621	2015
Gaussian Processes for Machine Learning CE Rasmussen, CKI Williams MIT Press, 2006	5472*	2006
Using the Nyström method to speed up kernel machines C Williams, M Seeger Advances in neural information processing systems 13, 2000	3128	2000
Gaussian processes for regression C Williams, C Rasmussen Advances in neural information processing systems 8, 1995	1974	1995
GTM: The generative topographic mapping CM Bishop, M Svensén, CKI Williams Neural computation 10 (1), 215-234, 1998	1933	1998
Multi-task Gaussian process prediction EV Bonilla, K Chai, C Williams Advances in neural information processing systems 20, 2007	1518	2007
Bayesian classification with Gaussian processes CKI Williams, D Barber IEEE Transactions on pattern analysis and machine intelligence 20 (12), 1342 …, 1998	1065	1998
Prediction with Gaussian processes: From linear regression to linear prediction and beyond CKI Williams Learning in graphical models, 599-621, 1998	993	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	671	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	534	2006
A framework for the quantitative evaluation of disentangled representations C Eastwood, CKI Williams 6th International Conference on Learning Representations, 2018	500	2018
Computing with infinite networks C Williams Advances in neural information processing systems 9, 1996	475	1996
Regression with input-dependent noise: A Gaussian process treatment P Goldberg, C Williams, C Bishop Advances in neural information processing systems 10, 1997	466	1997
On a connection between kernel PCA and metric multidimensional scaling C Williams Advances in neural information processing systems 13, 2000	351	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	335	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	321	2006
Harmonising chorales by probabilistic inference M Allan, C Williams Advances in neural information processing systems 17, 2004	278	2004
Developments of the generative topographic mapping CM Bishop, M Svensén, CKI Williams Neurocomputing 21 (1-3), 203-224, 1998	276	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	272	1996

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