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
Richard ZemelProfessor of Computer Science, University of TorontoVerified email at cs.toronto.edu
Sam Roweis (Memorial)New York UniversityVerified email at buffalo.edu
Babak ShahbabaStatistics and Computer Science, University of California, IrvineVerified email at uci.edu
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
Zoubin GhahramaniProfessor, University of Cambridge, and Distinguished Researcher, GoogleVerified email at eng.cam.ac.uk
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
Longhai LiUniversity of Saskatchewan, Saskatoon, SK, CANADAVerified email at usask.ca
Brian WyvillProfessor of Computer Science, University of Victoria, BCVerified email at cs.uvic.ca
Nicky BestProfessor of Statistics and Epidemiology, Imperial College LondonVerified email at imperial.ac.uk

Radford Neal

U Toronto *** GOOGLE SCHOLAR CAN GIVE WRONG PUBLICATION DATE/REFERENCE - LOOK AT ACTUAL PAPER/BOOK!

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	4569	1997
Bayesian learning for neural networks RM Neal Springer Science & Business Media, 1996	4385*	1996
Arithmetic coding for data compression IH Witten, RM Neal, JG Cleary Communications of the ACM 30 (6), 520-540, 1987	3921	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	3094	1998
Markov chain sampling methods for Dirichlet process mixture models RM Neal Journal of computational and graphical statistics 9 (2), 249-265, 2000	2716	2000
MCMC Using Hamiltonian Dynamics R Neal Handbook of Markov Chain Monte Carlo, 113-162, 2011	2215	2011
Slice sampling RM Neal Annals of statistics, 705-741, 2003	2183	2003
Probabilistic inference using Markov chain Monte Carlo methods RM Neal Department of Computer Science, University of Toronto, 1993	2039	1993
The helmholtz machine P Dayan, GE Hinton, RM Neal, RS Zemel Neural computation 7 (5), 889-904, 1995	1287	1995
Annealed importance sampling RM Neal Statistics and computing 11 (2), 125-139, 2001	1269	2001
The" wake-sleep" algorithm for unsupervised neural networks GE Hinton, P Dayan, BJ Frey, RM Neal Science 268 (5214), 1158-1161, 1995	1229	1995
Arithmetic coding revisited A Moffat, RM Neal, IH Witten ACM Transactions on Information Systems (TOIS) 16 (3), 256-294, 1998	782	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	691	1998
Connectionist learning of belief networks RM Neal Artificial intelligence 56 (1), 71-113, 1992	662	1992
Good codes based on very sparse matrices DJC MacKay, RM Neal IMA International Conference on Cryptography and Coding, 100-111, 1995	656	1995
Monte Carlo implementation of Gaussian process models for Bayesian regression and classification RM Neal arXiv preprint physics/9701026, 1997	513	1997
Regression and classification using Gaussian process priors RM Neal Bayesian Statistics 6, 1998	510*	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	509	2004
Sampling from multimodal distributions using tempered transitions RM Neal Statistics and computing 6 (4), 353-366, 1996	383	1996
Analysis of a nonreversible Markov chain sampler P Diaconis, S Holmes, RM Neal Annals of Applied Probability, 726-752, 2000	252	2000

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