Chris Williams

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Luc Van Goolprofessor computer vision ETH Zurich & KU Leuven, Head Toyota Lab TRACE @ KUL & ETHE-mail confirmado em ethz.ch
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. BishopDistinguished Scientist, 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
Geoffrey HintonEmeritus Prof. Comp Sci, U.Toronto & Engineering Fellow, GoogleE-mail confirmado em cs.toronto.edu
Matthias SeegerPrincipal Applied Scientist, Amazon, BerlinE-mail confirmado em amazon.de
Richard ZemelProfessor of Computer Science, University of TorontoE-mail confirmado em cs.toronto.edu
John QuinnGoogle Research, Sunbird AI, Makerere UniversityE-mail confirmado em cit.ac.ug
John Shawe-TaylorUCLE-mail confirmado em cs.ucl.ac.uk
David BarberDepartment of Computer Science, University College LondonE-mail confirmado em ucl.ac.uk
Michael MozerGoogle Research, Brain Team; University of ColoradoE-mail confirmado em colorado.edu
Jyri J. KivinenLapland University of Applied SciencesE-mail confirmado em lapinamk.fi
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 Head of SCEEM, University of BristolE-mail confirmado em bristol.ac.uk
Joaquin Quiñonero CandelaSenior Fellow, Harvard Belfer CenterE-mail confirmado em hks.harvard.edu
Volker TrespLudwig Maximilian University of Munich / München (LMU) and Siemens AGE-mail confirmado em dbs.ifi.lmu.de

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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
Gaussian processes for machine learning CE Rasmussen, CKI Williams MIT Press, 2006	27284	2006
Gaussian process for machine learning CE Rasmussen, CKI Williams MIT press, 2006	25605	2006
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	18493*	2010
The PASCAL visual object classes challenge 2007 (VOC2007) results M Everingham, A Zisserman, CKI Williams, L Van Gool, M Allan, ...	2618	2008
Using the Nyström method to speed up kernel machines C Williams, M Seeger Advances in neural information processing systems 13, 2000	2543	2000
GTM: The generative topographic mapping CM Bishop, M Svensén, CKI Williams Neural computation 10 (1), 215-234, 1998	1774	1998
Gaussian processes for regression C Williams, C Rasmussen Advances in neural information processing systems 8, 1995	1409	1995
Multi-task Gaussian process prediction EV Bonilla, K Chai, C Williams Advances in neural information processing systems 20, 2007	1081	2007
Bayesian classification with Gaussian processes CKI Williams, D Barber IEEE Transactions on pattern analysis and machine intelligence 20 (12), 1342 …, 1998	907	1998
Prediction with Gaussian processes: From linear regression to linear prediction and beyond CKI Williams Learning in graphical models, 599-621, 1998	829	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	536	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	485	2006
Computing with infinite networks C Williams Advances in neural information processing systems 9, 1996	478	1996
Gaussian processes for machine learning, vol. 2 CK Williams, CE Rasmussen MA: MIT press Cambridge, 2006	408	2006
Advances in neural information processing systems X Chen, Y Duan, R Houthooft, J Schulman, I Sutskever, P Abbeel, D Lee, ... Neural Information Processing Systems Fundation, Inc, 2015	396*	2015
Regression with input-dependent noise: A Gaussian process treatment P Goldberg, C Williams, C Bishop Advances in neural information processing systems 10, 1997	356	1997
The 2005 pascal visual object classes challenge M Everingham, A Zisserman, CKI Williams, LV Gool, M Allan, CM Bishop, ... Machine Learning Challenges Workshop, 117-176, 2005	324	2005
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	291	1996
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	287	2006
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 (3), 296-327, 2011	283	2011

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