Radford Neal

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Ian H. WittenProfessor of Computer Science, University of Waikato, New ZealandVerified email at waikato.ac.nz
Geoffrey HintonEmeritus Prof. Computer Science, University of TorontoVerified 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
W.R. PeltierProfessor of Physics, University of TorontoVerified email at atmosp.physics.utoronto.ca
Brendan FreyFounder & CEO, Deep Genomics; Co-Founder, Vector Institute; Professor, University of TorontoVerified email at psi.toronto.edu
Zoubin GhahramaniProfessor, University of Cambridge, and Distinguished Researcher, GoogleVerified email at eng.cam.ac.uk
Jennifer ListgartenProfessor, UC Berkeley EECS and Center for Computational BiologyVerified email at berkeley.edu
Bradley P. CarlinPharmaLex - USVerified email at counterpointstat.com
Andrew GelmanProfessor of Statistics and Political Science, Columbia UniversityVerified email at stat.columbia.edu
Alistair MoffatSchool of Computing and Information Systems, The University of MelbourneVerified email at unimelb.edu.au
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
Matthew J. BealChicago Trading CompanyVerified email at chicagotrading.com
Celia M.T. GreenwoodSenior Investigator, Lady Davis InstituteVerified email at mcgill.ca
Shuying SunTexas State UniversityVerified email at txstate.edu

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
Bayesian learning for neural networks RM Neal Springer Science & Business Media, 1995	6818*	1995
Near Shannon limit performance of low density parity check codes DJC MacKay, RM Neal Electronics letters 33 (6), 457-458, 1997	5210	1997
Arithmetic coding for data compression IH Witten, RM Neal, JG Cleary Communications of the ACM 30 (6), 520-540, 1987	4575	1987
MCMC Using Hamiltonian Dynamics R Neal Handbook of Markov Chain Monte Carlo, 113-162, 2011	4357	2011
A view of the EM algorithm that justifies incremental, sparse, and other variants RM Neal, GE Hinton Learning in graphical models, 355-368, 1998	3701	1998
Markov chain sampling methods for Dirichlet process mixture models RM Neal Journal of computational and graphical statistics 9 (2), 249-265, 2000	3254	2000
Slice sampling RM Neal Annals of statistics, 705-741, 2003	2880	2003
Probabilistic inference using Markov chain Monte Carlo methods RM Neal Department of Computer Science, University of Toronto, 1993	2406	1993
Annealed importance sampling RM Neal Statistics and computing 11, 125-139, 2001	1800	2001
The helmholtz machine P Dayan, GE Hinton, RM Neal, RS Zemel Neural computation 7 (5), 889-904, 1995	1733	1995
The" wake-sleep" algorithm for unsupervised neural networks GE Hinton, P Dayan, BJ Frey, RM Neal Science 268 (5214), 1158-1161, 1995	1564	1995
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	911	1998
Arithmetic coding revisited A Moffat, RM Neal, IH Witten ACM Transactions on Information Systems (TOIS) 16 (3), 256-294, 1998	863	1998
Connectionist learning of belief networks RM Neal Artificial intelligence 56 (1), 71-113, 1992	770	1992
Good codes based on very sparse matrices DJC MacKay, RM Neal IMA International Conference on Cryptography and Coding, 100-111, 1995	718	1995
Regression and classification using Gaussian process priors RM Neal Bayesian Statistics 6, 1998	686*	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	623	2004
Monte Carlo implementation of Gaussian process models for Bayesian regression and classification RM Neal arXiv preprint physics/9701026, 1997	623	1997
Priors for infinite networks RM Neal	483	1994
Sampling from multimodal distributions using tempered transitions RM Neal Statistics and computing 6, 353-366, 1996	464	1996

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