David MacKay

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Co-authors

H. K. D. H. BhadeshiaTata Steel Professor of Metallurgy, University of CambridgeVerified email at cam.ac.uk
Iain MurraySchool of Informatics, University of EdinburghVerified email at ed.ac.uk
Radford NealEmeritus Professor, Dept. of Statistics and Dept. of Computer Science, University of TorontoVerified email at utstat.toronto.edu
Ryan P. AdamsPrinceton UniversityVerified email at princeton.edu
Zoubin GhahramaniProfessor, University of Cambridge, and Distinguished Researcher, GoogleVerified email at eng.cam.ac.uk
Brendan FreyFounder & CEO, Deep Genomics; Co-Founder, Vector Institute; Professor, University of TorontoVerified email at psi.toronto.edu
Kenneth D. MillerProfessor of Neuroscience, Columbia UniversityVerified email at columbia.edu
Alan BlackwellProfessor of Interdisciplinary Design, University of CambridgeVerified email at cam.ac.uk
Oliver StegleGerman Cancer Research Center (DKFZ) & EMBL HeidelbergVerified email at dkfz.de
Tony RobinsonSpeechmatics (Cantab Research Limited)Verified email at tonyRobinson.com
Philip John WithersUniversity of ManchesterVerified email at manchester.ac.uk
Keith VertanenAssociate Professor, Michigan Technological UniversityVerified email at mtu.edu
Andrew M. ChildsJoint Center for Quantum Information and Computer Science, University of MarylandVerified email at umd.edu
Thore GraepelResearch Scientist, Google DeepMind, and Professor of Computer Science, UCLVerified email at ucl.ac.uk
John Paulin HansenProfessor, Technical University of DenmarkVerified email at dtu.dk
Dan Witzner HansenIT University of CopenhagenVerified email at itu.dk
Robert MacKayProfessor of Mathematics, University of WarwickVerified email at warwick.ac.uk

David MacKay

Professor of Natural Philosophy, Cavendish Laboratory, University of Cambridge

Verified email at mrao.cam.ac.uk - Homepage

Information Theory and Error-correcting Codes Reliable Computation with Unreliable Hardware Machine Learning and Bayesian Data Modelling Sustainable Energy and Public Understanding of Science


Title Sort by citations Sort by year Sort by title	Cited by Cited by	Year
Information theory, inference and learning algorithms DJC MacKay, DJC Mac Kay Cambridge university press, 2003	11434	2003
Information theory and reliable communication RG Gallager Wiley, 1968	8653	1968
Good error-correcting codes based on very sparse matrices DJC MacKay IEEE transactions on Information Theory 45 (2), 399-431, 1999	5190	1999
Bayesian interpolation DJC MacKay Neural computation 4 (3), 415-447, 1992	4720	1992
Near Shannon limit performance of low density parity check codes DJC MacKay, RM Neal Electronics letters 32 (18), 1645-1646, 1996	3326	1996
A practical Bayesian framework for backpropagation networks DJC MacKay Neural computation 4 (3), 448-472, 1992	2741	1992
Sustainable Energy-without the hot air D MacKay UIT cambridge, 2008	2066	2008
Low density parity check codes over GF (q) MC Davey, DJC MacKay 1998 Information Theory Workshop (Cat. No. 98EX131), 70-71, 1998	1533	1998
Fountain codes DJC MacKay IEE Proceedings-Communications 152 (6), 1062-1068, 2005	1417	2005
Information-based objective functions for active data selection DJC MacKay Neural computation 4 (4), 590-604, 1992	1352	1992
Near Shannon limit performance of low density parity check codes DJC MacKay, RM Neal Electronics letters 33 (6), 457-458, 1997	1258	1997
Turbo decoding as an instance of Pearl's" belief propagation" algorithm RJ McEliece, DJC MacKay, JF Cheng IEEE Journal on selected areas in communications 16 (2), 140-152, 1998	1170	1998
Introduction to Gaussian processes DJC MacKay NATO ASI Series F Computer and Systems Sciences 168, 133-166, 1998	1053	1998
Probable networks and plausible predictions—a review of practical Bayesian methods for supervised neural networks DJC MacKay Network: computation in neural systems 6 (3), 469-505, 1995	1006	1995
The evidence framework applied to classification networks DJC MacKay Neural computation 4 (5), 720-736, 1992	874	1992
Bayesian methods for adaptive models DJC MacKay California Institute of Technology, 1992	827	1992
Introduction to monte carlo methods DJC Mackay Learning in graphical models, 175-204, 1998	665	1998
Good codes based on very sparse matrices DJC MacKay, RM Neal IMA International Conference on Cryptography and Coding, 100-111, 1995	630	1995
Bayesian online changepoint detection RP Adams, DJC MacKay arXiv preprint arXiv:0710.3742, 2007	570	2007
Bayesian nonlinear modeling for the prediction competition DJC MacKay ASHRAE transactions 100 (2), 1053-1062, 1994	557	1994

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