Chris Williams

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Coauteurs

Luc Van Goolprofessor computer vision INSAIT Sofia University, em. KU Leuven, em. ETHZ, Toyota Lab TRACEAdresse e-mail validée de insait.ai
Andrew ZissermanUniversity of OxfordAdresse e-mail validée de robots.ox.ac.uk
Carl Edward RasmussenProfessor of Machine Learning, University of CambridgeAdresse e-mail validée de cam.ac.uk
S. M. Ali EslamiGoogle DeepMindAdresse e-mail validée de google.com
Christopher M. BishopTechnical Fellow, Microsoft Research, Cambridge, U.K.Adresse e-mail validée de microsoft.com
Edwin V. BonillaPrincipal Research Scientist, CSIRO's Data61Adresse e-mail validée de data61.csiro.au
Matthias SeegerPrincipal Applied Scientist, Amazon, BerlinAdresse e-mail validée de amazon.de
Geoffrey HintonEmeritus Prof. Computer Science, University of TorontoAdresse e-mail validée de cs.toronto.edu
John Shawe-TaylorUCLAdresse e-mail validée de cs.ucl.ac.uk
John QuinnGoogle Research, Sunbird AI, Makerere UniversityAdresse e-mail validée de cit.ac.ug
Richard ZemelProfessor of Computer Science, University of TorontoAdresse e-mail validée de cs.toronto.edu
David BarberDepartment of Computer Science, University College LondonAdresse e-mail validée de ucl.ac.uk
Michael MozerGoogle DeepMind; University of ColoradoAdresse e-mail validée de colorado.edu
Neil D. LawrenceUniversity of CambridgeAdresse e-mail validée de cl.cam.ac.uk
Marc ToussaintProfessor of Computer Science, TU Berlin, GermanyAdresse e-mail validée de tu-berlin.de
Miguel Á. Carreira-PerpiñánProfessor of Computer Science, University of California, MercedAdresse e-mail validée de ucmerced.edu
Ian T. NabneyProfessor and Associate Dean, Faculty of Science and Engineering, University of BristolAdresse e-mail validée de bristol.ac.uk
Joaquin Quiñonero CandelaOpenAIAdresse e-mail validée de openai.com
Volker TrespLudwig-Maximilians-Universität München (LMU Munich)Adresse e-mail validée de dbs.ifi.lmu.de
Sethu VijayakumarProfessor of Robotics, University of Edinburgh; Programme Director at The Alan Turing Institute, UKAdresse e-mail validée de ed.ac.uk

Suivre

Chris Williams

Professor of Machine Learning, University of Edinburgh

Adresse e-mail validée de inf.ed.ac.uk

Machine learning pattern recognition computer vision


Titre Trier par citations Trier par année Trier par titre	Citée par Citée par	Année
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	24810	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	11248	2015
Gaussian Processes for Machine Learning CE Rasmussen, CKI Williams MIT Press, 2006	6701*	2006
Using the Nyström method to speed up kernel machines C Williams, M Seeger Advances in neural information processing systems 13, 2000	3179	2000
Gaussian processes for regression C Williams, C Rasmussen Advances in neural information processing systems 8, 1995	2071	1995
GTM: The generative topographic mapping CM Bishop, M Svensén, CKI Williams Neural computation 10 (1), 215-234, 1998	1953	1998
Multi-task Gaussian process prediction EV Bonilla, K Chai, C Williams Advances in neural information processing systems 20, 2007	1573	2007
Bayesian classification with Gaussian processes CKI Williams, D Barber IEEE Transactions on pattern analysis and machine intelligence 20 (12), 1342 …, 1998	1092	1998
Prediction with Gaussian processes: From linear regression to linear prediction and beyond CKI Williams Learning in graphical models, 599-621, 1998	1013	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	880	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	676	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	537	2006
A framework for the quantitative evaluation of disentangled representations C Eastwood, CKI Williams 6th International Conference on Learning Representations, 2018	528	2018
Computing with infinite networks C Williams Advances in neural information processing systems 9, 1996	493	1996
Regression with input-dependent noise: A Gaussian process treatment P Goldberg, C Williams, C Bishop Advances in neural information processing systems 10, 1997	476	1997
On a connection between kernel PCA and metric multidimensional scaling C Williams Advances in neural information processing systems 13, 2000	355	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	343	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	306	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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