Chris Williams

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Andrew ZissermanUniversity of OxfordPreverjeni e-poštni naslov na robots.ox.ac.uk
Luc Van Goolprofessor computer vision INSAIT Sofia University, em. KU Leuven, em. ETHZ, Toyota Lab TRACEPreverjeni e-poštni naslov na insait.ai
Carl Edward RasmussenProfessor of Machine Learning, University of CambridgePreverjeni e-poštni naslov na cam.ac.uk
S. M. Ali EslamiGoogle DeepMindPreverjeni e-poštni naslov na google.com
Christopher M. BishopTechnical Fellow, Microsoft Research, Cambridge, U.K.Preverjeni e-poštni naslov na microsoft.com
Edwin V. BonillaPrincipal Research Scientist, CSIRO's Data61Preverjeni e-poštni naslov na data61.csiro.au
Geoffrey HintonEmeritus Prof. Computer Science, University of TorontoPreverjeni e-poštni naslov na cs.toronto.edu
Matthias SeegerPrincipal Applied Scientist, Amazon, BerlinPreverjeni e-poštni naslov na amazon.de
John Shawe-TaylorUCLPreverjeni e-poštni naslov na cs.ucl.ac.uk
John QuinnGoogle Research, Sunbird AI, Makerere UniversityPreverjeni e-poštni naslov na cit.ac.ug
Richard ZemelProfessor of Computer Science, University of TorontoPreverjeni e-poštni naslov na cs.toronto.edu
David BarberDepartment of Computer Science, University College LondonPreverjeni e-poštni naslov na ucl.ac.uk
Michael MozerGoogle DeepMind; University of ColoradoPreverjeni e-poštni naslov na colorado.edu
Neil D. LawrenceUniversity of CambridgePreverjeni e-poštni naslov na cl.cam.ac.uk
Marc ToussaintProfessor of Computer Science, TU Berlin, GermanyPreverjeni e-poštni naslov na tu-berlin.de
Miguel Á. Carreira-PerpiñánProfessor of Computer Science, University of California, MercedPreverjeni e-poštni naslov na ucmerced.edu
Ian T. NabneyProfessor and Associate Dean, Faculty of Science and Engineering, University of BristolPreverjeni e-poštni naslov na bristol.ac.uk
Joaquin Quiñonero CandelaOpenAIPreverjeni e-poštni naslov na openai.com
Volker TrespLudwig-Maximilians-Universität München (LMU Munich)Preverjeni e-poštni naslov na dbs.ifi.lmu.de
Sethu VijayakumarProfessor of Robotics, University of Edinburgh; Programme Director at The Alan Turing Institute, UKPreverjeni e-poštni naslov na ed.ac.uk

Spremljaj

Chris Williams

Professor of Machine Learning, University of Edinburgh

Preverjeni e-poštni naslov na inf.ed.ac.uk

Machine learning pattern recognition computer vision


Naslov Razvrsti po navedbah Razvrsti po letniku Razvrsti po naslovu	Navedeno Navedeno	Leto
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	24634	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	11890	2015
Gaussian Processes for Machine Learning CE Rasmussen, CKI Williams MIT Press, 2006	5727*	2006
Using the Nyström method to speed up kernel machines C Williams, M Seeger Advances in neural information processing systems 13, 2000	3174	2000
Gaussian processes for regression C Williams, C Rasmussen Advances in neural information processing systems 8, 1995	2045	1995
GTM: The generative topographic mapping CM Bishop, M Svensén, CKI Williams Neural computation 10 (1), 215-234, 1998	1943	1998
Multi-task Gaussian process prediction EV Bonilla, K Chai, C Williams Advances in neural information processing systems 20, 2007	1561	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	1005	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	684	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	523	2018
Computing with infinite networks C Williams Advances in neural information processing systems 9, 1996	486	1996
Regression with input-dependent noise: A Gaussian process treatment P Goldberg, C Williams, C Bishop Advances in neural information processing systems 10, 1997	470	1997
On a connection between kernel PCA and metric multidimensional scaling C Williams Advances in neural information processing systems 13, 2000	353	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	341	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
Developments of the generative topographic mapping CM Bishop, M Svensén, CKI Williams Neurocomputing 21 (1-3), 203-224, 1998	281	1998
Harmonising chorales by probabilistic inference M Allan, C Williams Advances in neural information processing systems 17, 2004	276	2004
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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