Chris Williams

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Andrew ZissermanUniversity of OxfordEmail verificata su robots.ox.ac.uk
Luc Van Goolprofessor computer vision INSAIT Sofia University, em. KU Leuven, em. ETHZ, Toyota Lab TRACEEmail verificata su insait.ai
Carl Edward RasmussenProfessor of Machine Learning, University of CambridgeEmail verificata su cam.ac.uk
S. M. Ali EslamiGoogle DeepMindEmail verificata su google.com
Christopher M. BishopTechnical Fellow, Microsoft Research, Cambridge, U.K.Email verificata su microsoft.com
Edwin V. BonillaPrincipal Research Scientist, CSIRO's Data61Email verificata su data61.csiro.au
Geoffrey HintonEmeritus Prof. Computer Science, University of TorontoEmail verificata su cs.toronto.edu
Matthias SeegerPrincipal Applied Scientist, Amazon, BerlinEmail verificata su amazon.de
John Shawe-TaylorUCLEmail verificata su cs.ucl.ac.uk
John QuinnGoogle Research, Sunbird AI, Makerere UniversityEmail verificata su cit.ac.ug
Richard ZemelProfessor of Computer Science, University of TorontoEmail verificata su cs.toronto.edu
David BarberDepartment of Computer Science, University College LondonEmail verificata su ucl.ac.uk
Michael MozerGoogle DeepMind; University of ColoradoEmail verificata su colorado.edu
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 Á. Carreira-PerpiñánProfessor of Computer Science, University of California, MercedEmail verificata su ucmerced.edu
Ian T. NabneyProfessor and Associate Dean, Faculty of Science and Engineering, University of BristolEmail verificata su bristol.ac.uk
Joaquin Quiñonero CandelaOpenAIEmail verificata su openai.com
Volker TrespLudwig-Maximilians-Universität München (LMU Munich)Email verificata su dbs.ifi.lmu.de
Sethu VijayakumarProfessor of Robotics, University of Edinburgh; Programme Director at The Alan Turing Institute, UKEmail verificata su ed.ac.uk

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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
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	23888	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	11577	2015
Gaussian processes for machine learning CE Rasmussen, CKI Williams MIT Press, 2006	5437*	2006
Using the Nyström method to speed up kernel machines C Williams, M Seeger Advances in neural information processing systems 13, 2000	3123	2000
Gaussian processes for regression C Williams, C Rasmussen Advances in neural information processing systems 8, 1995	1971	1995
GTM: The generative topographic mapping CM Bishop, M Svensén, CKI Williams Neural computation 10 (1), 215-234, 1998	1930	1998
Multi-task Gaussian process prediction EV Bonilla, K Chai, C Williams Advances in neural information processing systems 20, 2007	1517	2007
Bayesian classification with Gaussian processes CKI Williams, D Barber IEEE Transactions on pattern analysis and machine intelligence 20 (12), 1342 …, 1998	1064	1998
Prediction with Gaussian processes: From linear regression to linear prediction and beyond CKI Williams Learning in graphical models, 599-621, 1998	992	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	670	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	533	2006
A framework for the quantitative evaluation of disentangled representations C Eastwood, CKI Williams 6th International Conference on Learning Representations, 2018	499	2018
Computing with infinite networks C Williams Advances in neural information processing systems 9, 1996	473	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	277	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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