Radford Neal
Radford Neal
Emeritus Professor, Dept. of Statistics and Dept. of Computer Science, University of Toronto
Verified email at utstat.toronto.edu - Homepage
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
44101997
Bayesian learning for neural networks
RM Neal
Springer Science & Business Media, 1996
3998*1996
Arithmetic coding for data compression
IH Witten, RM Neal, JG Cleary
Communications of the ACM 30 (6), 520-540, 1987
38931987
A view of the EM algorithm that justifies incremental, sparse, and other variants
RM Neal, GE Hinton
Learning in graphical models, 355-368, 1998
29361998
Markov chain sampling methods for Dirichlet process mixture models
RM Neal
Journal of computational and graphical statistics 9 (2), 249-265, 2000
25872000
Slice sampling
RM Neal
Annals of statistics, 705-741, 2003
20292003
Probabilistic inference using Markov chain Monte Carlo methods
RM Neal
Department of Computer Science, University of Toronto, 1993
19431993
MCMC Using Hamiltonian Dynamics
R Neal
Handbook of Markov Chain Monte Carlo, 113-162, 2011
19222011
Annealed importance sampling
RM Neal
Statistics and computing 11 (2), 125-139, 2001
12022001
The helmholtz machine
P Dayan, GE Hinton, RM Neal, RS Zemel
Neural computation 7 (5), 889-904, 1995
11931995
The" wake-sleep" algorithm for unsupervised neural networks
GE Hinton, P Dayan, BJ Frey, RM Neal
Science 268 (5214), 1158-1161, 1995
10811995
Arithmetic coding revisited
A Moffat, RM Neal, IH Witten
ACM Transactions on Information Systems (TOIS) 16 (3), 256-294, 1998
7701998
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
6541998
Connectionist learning of belief networks
RM Neal
Artificial intelligence 56 (1), 71-113, 1992
6161992
Good codes based on very sparse matrices
DJC MacKay, RM Neal
IMA International Conference on Cryptography and Coding, 100-111, 1995
6031995
Regression and classification using Gaussian process priors
RM Neal
Bayesian Statistics 6, 1998
493*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
4892004
Monte Carlo implementation of Gaussian process models for Bayesian regression and classification
RM Neal
arXiv preprint physics/9701026, 1997
4791997
Sampling from multimodal distributions using tempered transitions
RM Neal
Statistics and computing 6 (4), 353-366, 1996
3751996
Analysis of a nonreversible Markov chain sampler
P Diaconis, S Holmes, RM Neal
Annals of Applied Probability, 726-752, 2000
2332000
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