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
44621997
Bayesian learning for neural networks
RM Neal
Springer Science & Business Media, 1996
4132*1996
Arithmetic coding for data compression
IH Witten, RM Neal, JG Cleary
Communications of the ACM 30 (6), 520-540, 1987
39221987
A view of the EM algorithm that justifies incremental, sparse, and other variants
RM Neal, GE Hinton
Learning in graphical models, 355-368, 1998
29671998
Markov chain sampling methods for Dirichlet process mixture models
RM Neal
Journal of computational and graphical statistics 9 (2), 249-265, 2000
26292000
Slice sampling
RM Neal
Annals of statistics, 705-741, 2003
20732003
MCMC Using Hamiltonian Dynamics
R Neal
Handbook of Markov Chain Monte Carlo, 113-162, 2011
20182011
Probabilistic inference using Markov chain Monte Carlo methods
RM Neal
Department of Computer Science, University of Toronto, 1993
19681993
Annealed importance sampling
RM Neal
Statistics and computing 11 (2), 125-139, 2001
12212001
The helmholtz machine
P Dayan, GE Hinton, RM Neal, RS Zemel
Neural computation 7 (5), 889-904, 1995
12171995
The" wake-sleep" algorithm for unsupervised neural networks
GE Hinton, P Dayan, BJ Frey, RM Neal
Science 268 (5214), 1158-1161, 1995
11081995
Arithmetic coding revisited
A Moffat, RM Neal, IH Witten
ACM Transactions on Information Systems (TOIS) 16 (3), 256-294, 1998
7731998
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
6751998
Connectionist learning of belief networks
RM Neal
Artificial intelligence 56 (1), 71-113, 1992
6331992
Good codes based on very sparse matrices
DJC MacKay, RM Neal
IMA International Conference on Cryptography and Coding, 100-111, 1995
6121995
Regression and classification using Gaussian process priors
RM Neal
Bayesian Statistics 6, 1998
501*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
4962004
Monte Carlo implementation of Gaussian process models for Bayesian regression and classification
RM Neal
arXiv preprint physics/9701026, 1997
4881997
Sampling from multimodal distributions using tempered transitions
RM Neal
Statistics and computing 6 (4), 353-366, 1996
3831996
Analysis of a nonreversible Markov chain sampler
P Diaconis, S Holmes, RM Neal
Annals of Applied Probability, 726-752, 2000
2372000
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