Chris Williams

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Luc Van Goolprofessor computer vision INSAIT Sofia University, em. KU Leuven, em. ETHZ, Toyota Lab TRACEE-mail confirmado em insait.ai
Andrew ZissermanUniversity of OxfordE-mail confirmado em robots.ox.ac.uk
Carl Edward RasmussenProfessor of Machine Learning, University of CambridgeE-mail confirmado em cam.ac.uk
S. M. Ali EslamiGoogle DeepMindE-mail confirmado em google.com
Christopher M. BishopTechnical Fellow, Microsoft Research, Cambridge, U.K.E-mail confirmado em microsoft.com
Edwin V. BonillaPrincipal Research Scientist, CSIRO's Data61E-mail confirmado em data61.csiro.au
Matthias SeegerPrincipal Applied Scientist, Amazon, BerlinE-mail confirmado em amazon.de
Geoffrey HintonEmeritus Prof. Computer Science, University of TorontoE-mail confirmado em cs.toronto.edu
John Shawe-TaylorUCLE-mail confirmado em cs.ucl.ac.uk
John QuinnGoogle Research, Sunbird AI, Makerere UniversityE-mail confirmado em cit.ac.ug
Richard ZemelProfessor of Computer Science, University of TorontoE-mail confirmado em cs.toronto.edu
David BarberDepartment of Computer Science, University College LondonE-mail confirmado em ucl.ac.uk
Michael MozerGoogle DeepMind; University of ColoradoE-mail confirmado em colorado.edu
Neil D. LawrenceUniversity of CambridgeE-mail confirmado em cl.cam.ac.uk
Marc ToussaintProfessor of Computer Science, TU Berlin, GermanyE-mail confirmado em tu-berlin.de
Miguel Á. Carreira-PerpiñánProfessor of Computer Science, University of California, MercedE-mail confirmado em ucmerced.edu
Ian T. NabneyProfessor and Associate Dean, Faculty of Science and Engineering, University of BristolE-mail confirmado em bristol.ac.uk
Joaquin Quiñonero CandelaOpenAIE-mail confirmado em openai.com
Volker TrespLudwig-Maximilians-Universität München (LMU Munich)E-mail confirmado em dbs.ifi.lmu.de
Sethu VijayakumarProfessor of Robotics, University of Edinburgh; Programme Director at The Alan Turing Institute, UKE-mail confirmado em ed.ac.uk

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Chris Williams

Professor of Machine Learning, University of Edinburgh

E-mail confirmado em inf.ed.ac.uk

Machine learning pattern recognition computer vision


Título Ordenar por citações Ordenar por ano Ordenar por título	Citado por Citado por	Ano
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	24576	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	11159	2015
Gaussian Processes for Machine Learning CE Rasmussen, CKI Williams MIT Press, 2006	6609*	2006
Using the Nyström method to speed up kernel machines C Williams, M Seeger Advances in neural information processing systems 13, 2000	3162	2000
Gaussian processes for regression C Williams, C Rasmussen Advances in neural information processing systems 8, 1995	2051	1995
GTM: The generative topographic mapping CM Bishop, M Svensén, CKI Williams Neural computation 10 (1), 215-234, 1998	1950	1998
Multi-task Gaussian process prediction EV Bonilla, K Chai, C Williams Advances in neural information processing systems 20, 2007	1555	2007
Bayesian classification with Gaussian processes CKI Williams, D Barber IEEE Transactions on pattern analysis and machine intelligence 20 (12), 1342 …, 1998	1086	1998
Prediction with Gaussian processes: From linear regression to linear prediction and beyond CKI Williams Learning in graphical models, 599-621, 1998	1006	1998
Advances in neural information processing systems CKI Williams, CE Rasmussen Nobili F, Mazzei D, Dessi B, Morbelli S, Brugnolo A, Barbieri P, 18131821, 1996	879	1996
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	675	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	536	2006
A framework for the quantitative evaluation of disentangled representations C Eastwood, CKI Williams 6th International Conference on Learning Representations, 2018	520	2018
Computing with infinite networks C Williams Advances in neural information processing systems 9, 1996	490	1996
Regression with input-dependent noise: A Gaussian process treatment P Goldberg, C Williams, C Bishop Advances in neural information processing systems 10, 1997	474	1997
On a connection between kernel PCA and metric multidimensional scaling C Williams Advances in neural information processing systems 13, 2000	354	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	340	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	319	2006
Covariance functions CE Rasmussen, CKI Williams MIT press, 2005	303	2005
Developments of the generative topographic mapping CM Bishop, M Svensén, CKI Williams Neurocomputing 21 (1-3), 203-224, 1998	283	1998

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