Chris Williams

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	Tutte	Dal 2016
Citazioni	56727	33547
Indice H	57	40
i10-index	140	85

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Andrew ZissermanUniversity of OxfordEmail verificata su robots.ox.ac.uk
Luc Van Goolprofessor computer vision ETH Zurich & KU Leuven, Head Toyota Lab TRACE @ KUL & ETHEmail verificata su ethz.ch
Carl Edward RasmussenProfessor of Machine Learning, University of CambridgeEmail verificata su cam.ac.uk
Christopher M. BishopDistinguished Scientist, Microsoft Research, Cambridge, U.K.Email verificata su microsoft.com
S. M. Ali EslamiGoogle DeepMindEmail verificata su google.com
Edwin V. BonillaPrincipal Research Scientist, CSIRO's Data61Email verificata su data61.csiro.au
Geoffrey HintonEmeritus Prof. Comp Sci, U.Toronto & Engineering Fellow, GoogleEmail verificata su cs.toronto.edu
Matthias SeegerPrincipal Applied Scientist, Amazon, BerlinEmail verificata su amazon.de
John QuinnGoogle AI Ghana, Makerere UniversityEmail verificata su cit.ac.ug
David BarberDepartment of Computer Science, University College LondonEmail verificata su ucl.ac.uk
Richard ZemelProfessor of Computer Science, University of TorontoEmail verificata su cs.toronto.edu
John Shawe-TaylorUCLEmail verificata su cs.ucl.ac.uk
Michael MozerGoogle Research, Brain Team; University of ColoradoEmail verificata su colorado.edu
Jyri J. KivinenGE HealthcareEmail verificata su ge.com
Neil D. LawrenceUniversity of CambridgeEmail verificata su cl.cam.ac.uk
Marc ToussaintProfessor of Computer Science, TU Berlin, GermanyEmail verificata su tu-berlin.de
Miguel A. Carreira-PerpinanProfessor of Computer Science, University of California, MercedEmail verificata su ucmerced.edu
Ian T. NabneyProfessor and Head of SCEEM, University of BristolEmail verificata su bristol.ac.uk
Joaquin Quiñonero CandelaDistinguished Tech Lead for Responsible AI at FacebookEmail verificata su fb.com
Volker TrespLudwig Maximilian University of Munich / München (LMU) and Siemens AGEmail verificata su dbs.ifi.lmu.de

Chris Williams

Professor of Machine Learning, University of Edinburgh

Email verificata su inf.ed.ac.uk

Machine learning pattern recognition computer vision


Titolo Ordina per citazioni Ordina per anno Ordina per titolo	Citata da Citata da	Anno
Gaussian processes for machine learning CE Rasmussen, CKI Williams MIT Press, 2006	22336	2006
Gaussian process for machine learning CE Rasmussen, CKI Williams MIT press, 2006	20833	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	10468	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 (1), 98-136, 2015	3319	2015
The PASCAL visual object classes challenge 2007 (VOC2007) results M Everingham, L Van Gool, CKI Williams, J Winn, A Zisserman	2665	2007
Using the Nyström method to speed up kernel machines C Williams, M Seeger Proceedings of the 14th annual conference on neural information processing …, 2001	2296	2001
GTM: The generative topographic mapping CM Bishop, M Svensén, CKI Williams Neural computation 10 (1), 215-234, 1998	1712	1998
Gaussian processes for regression CKI Williams, CE Rasmussen MIT, 1996	1248	1996
Multi-task Gaussian process prediction C Williams, EV Bonilla, KM Chai Advances in neural information processing systems, 153-160, 2007	929	2007
Bayesian classification with Gaussian processes CKI Williams, D Barber IEEE Transactions on Pattern Analysis and Machine Intelligence 20 (12), 1342 …, 1998	852	1998
Prediction with Gaussian processes: From linear regression to linear prediction and beyond CKI Williams Learning in graphical models, 599-621, 1998	773	1998
Fast forward selection to speed up sparse Gaussian process regression M Seeger, C Williams, N Lawrence Artificial Intelligence and Statistics 9, 2003	491	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	463	2006
Regression with input-dependent noise: A Gaussian process treatment PW Goldberg, CKI Williams, CM Bishop Advances in neural information processing systems 10, 493-499, 1997	322	1997
The 2005 pascal visual object classes challenge M Everingham, A Zisserman, CKI Williams, L Van Gool, M Allan, ... Machine Learning Challenges Workshop, 117-176, 2005	297	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	269	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	265	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	233	2011
GTM: A principled alternative to the self-organizing map CM Bishop, M Svensén, CKI Williams International Conference on Artificial Neural Networks, 165-170, 1996	232	1996
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	232	1996

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