Radford Neal

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Ian H. WittenProfessor of Computer Science, University of Waikato, New ZealandVerified email at cs.waikato.ac.nz
Geoffrey HintonEmeritus Prof. Comp Sci, U.Toronto & Engineering Fellow, GoogleVerified email at cs.toronto.edu
David MacKayProfessor of Natural Philosophy, Cavendish Laboratory, University of CambridgeVerified email at mrao.cam.ac.uk
Sam Roweis (Memorial)New York UniversityVerified email at buffalo.edu
Babak ShahbabaStatistics and Computer Science, University of California, IrvineVerified email at uci.edu
Richard ZemelProfessor of Computer Science, University of TorontoVerified email at cs.toronto.edu
Zoubin GhahramaniProfessor, University of Cambridge, and Chief Scientist, UberVerified email at eng.cam.ac.uk
Brendan FreyFounder & CEO, Deep Genomics; Co-Founder, Vector Institute; Professor, University of TorontoVerified email at psi.toronto.edu
Jennifer ListgartenProfessor, UC Berkeley EECS and Center for Computational BiologyVerified email at berkeley.edu
W.R. PeltierProfessor of Physics, University of TorontoVerified email at atmosp.physics.utoronto.ca
Alistair MoffatSchool of Computing and Information Systems, The University of MelbourneVerified email at unimelb.edu.au
Bradley P. CarlinCounterpoint Statistical Consulting, LLCVerified email at counterpointstat.com
Robert E. KassCarnegie Mellon UniversityVerified email at stat.cmu.edu
Andrew GelmanProfessor of Statistics and Political Science, Columbia UniversityVerified email at stat.columbia.edu
Andrew EmiliBoston University (formerly University of Toronto)Verified email at bu.edu
Susan P HolmesProfessor of Statistics, Stanford UniversityVerified email at stat.stanford.edu
Edward MeedsMicrosoft Research CambridgeVerified email at microsoft.com
Brian WyvillProfessor of Computer Science, University of Victoria, BCVerified email at cs.uvic.ca
Longhai LiUniversity of Saskatchewan, Saskatoon, SK, CANADAVerified email at usask.ca
Nicky BestProfessor of Statistics and Epidemiology, Imperial College LondonVerified email at imperial.ac.uk

Radford Neal

Emeritus Professor, Dept. of Statistics and Dept. of Computer Science, University of Toronto

Verified email at utstat.toronto.edu - Homepage

Bayesian inference Monte Carlo methods Information theory Machine learning Neural networks


Title Sort by citations Sort by year Sort by title	Cited by Cited by	Year
Near Shannon limit performance of low density parity check codes DJC MacKay, RM Neal Electronics letters 33 (6), 457-458, 1997	4491	1997
Bayesian learning for neural networks RM Neal Springer Science & Business Media, 1996	4229*	1996
Arithmetic coding for data compression IH Witten, RM Neal, JG Cleary Communications of the ACM 30 (6), 520-540, 1987	3938	1987
A view of the EM algorithm that justifies incremental, sparse, and other variants RM Neal, GE Hinton Learning in graphical models, 355-368, 1998	3007	1998
Markov chain sampling methods for Dirichlet process mixture models RM Neal Journal of computational and graphical statistics 9 (2), 249-265, 2000	2661	2000
Slice sampling RM Neal Annals of statistics, 705-741, 2003	2107	2003
MCMC Using Hamiltonian Dynamics R Neal Handbook of Markov Chain Monte Carlo, 113-162, 2011	2092	2011
Probabilistic inference using Markov chain Monte Carlo methods RM Neal Department of Computer Science, University of Toronto, 1993	1990	1993
Annealed importance sampling RM Neal Statistics and computing 11 (2), 125-139, 2001	1249	2001
The helmholtz machine P Dayan, GE Hinton, RM Neal, RS Zemel Neural computation 7 (5), 889-904, 1995	1240	1995
The" wake-sleep" algorithm for unsupervised neural networks GE Hinton, P Dayan, BJ Frey, RM Neal Science 268 (5214), 1158-1161, 1995	1128	1995
Arithmetic coding revisited A Moffat, RM Neal, IH Witten ACM Transactions on Information Systems (TOIS) 16 (3), 256-294, 1998	779	1998
Markov chain Monte Carlo in practice: a roundtable discussion RE Kass, BP Carlin, A Gelman, RM Neal The American Statistician 52 (2), 93-100, 1998	686	1998
Connectionist learning of belief networks RM Neal Artificial intelligence 56 (1), 71-113, 1992	647	1992
Good codes based on very sparse matrices DJC MacKay, RM Neal IMA International Conference on Cryptography and Coding, 100-111, 1995	620	1995
Regression and classification using Gaussian process priors RM Neal Bayesian Statistics 6, 1998	506*	1998
A split-merge Markov chain Monte Carlo procedure for the Dirichlet process mixture model S Jain, RM Neal Journal of Computational and Graphical Statistics, 2004	503	2004
Monte Carlo implementation of Gaussian process models for Bayesian regression and classification RM Neal arXiv preprint physics/9701026, 1997	499	1997
Sampling from multimodal distributions using tempered transitions RM Neal Statistics and computing 6 (4), 353-366, 1996	387	1996
Analysis of a nonreversible Markov chain sampler P Diaconis, S Holmes, RM Neal Annals of Applied Probability, 726-752, 2000	241	2000

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