Radford M. Neal

35 papers A 1B 1Journal 23Unranked 6
YearRankTypeTitle / Venue / Authors
2025 J jnl
Efficiency of reversible MCMC methods: elementary derivations and applications to composite methods.
J. Appl. Probab.
Radford M. Neal, Jeffrey S. Rosenthal
2020 J jnl
Non-reversibly updating a uniform [0, 1] value for Metropolis accept/reject decisions.
CoRR
Radford M. Neal
2015 J jnl
Fast exact summation using small and large superaccumulators.
CoRR
Radford M. Neal
2015 J jnl
Representing numeric data in 32 bits while preserving 64-bit precision.
CoRR
Radford M. Neal
2014 J jnl
Split Hamiltonian Monte Carlo.
Stat. Comput.
Babak Shahbaba, Shiwei Lan, Wesley O. Johnson, Radford M. Neal
2013 J jnl
Inference for Belief Networks Using Coupling From the Past
CoRR
Michael Harvey, Radford M. Neal
2012 J jnl
Gaussian Process Regression with Heteroscedastic or Non-Gaussian Residuals
CoRR
Chunyi Wang, Radford M. Neal
2011 J jnl
On Deducing Conditional Independence from d-Separation in Causal Graphs with Feedback (Research Note)
CoRR
Radford M. Neal
2009 J jnl
Nonlinear Models Using Dirichlet Process Mixtures.
J. Mach. Learn. Res.
Babak Shahbaba, Radford M. Neal
2007 J jnl
Difference detection in LC-MS data for protein biomarker discovery.
Bioinform.
Jennifer Listgarten, Radford M. Neal, Sam T. Roweis, Peter Wong, Andrew Emili
2007 J jnl
Pattern Recognition and Machine Learning.
Technometrics
Radford M. Neal
2006 — conf
Bayesian Detection of Infrequent Differences in Sets of Time Series with Shared Structure.
NIPS
Jennifer Listgarten, Radford M. Neal, Sam T. Roweis, Rachel Puckrin, Sean Cutler
2006 J jnl
Gene function classification using Bayesian models with hierarchy-based priors.
BMC Bioinform.
Babak Shahbaba, Radford M. Neal
2006 — ch.
High Dimensional Classification with Bayesian Neural Networks and Dirichlet Diffusion Trees.
Feature Extraction
Radford M. Neal, Jianguo Zhang
2006 — conf
Modeling Dyadic Data with Binary Latent Factors.
NIPS
Edward Meeds, Zoubin Ghahramani, Radford M. Neal, Sam T. Roweis
2005 — conf
Classification with Bayesian Neural Networks.
MLCW
Radford M. Neal
2004 — conf
Multiple Alignment of Continuous Time Series.
NIPS
Jennifer Listgarten, Radford M. Neal, Sam T. Roweis, Andrew Emili
2003 — conf
Inferring State Sequences for Non-linear Systems with Embedded Hidden Markov Models.
NIPS
Radford M. Neal, Matthew J. Beal, Sam T. Roweis
2001 J jnl
Annealed importance sampling.
Stat. Comput.
Radford M. Neal
2000 A conf
Inference for Belief Networks Using Coupling From the Past.
UAI
Michael Harvey, Radford M. Neal
2000 J jnl
On Deducing Conditional Independence from d-Separation in Causal Graphs with Feedback (Research Note).
J. Artif. Intell. Res.
Radford M. Neal
1998 — ch.
A View of the Em Algorithm that Justifies Incremental, Sparse, and other Variants.
Learning in Graphical Models
Radford M. Neal, Geoffrey E. Hinton
1998 J jnl
Arithmetic Coding Revisited.
ACM Trans. Inf. Syst.
Alistair Moffat, Radford M. Neal, Ian H. Witten
1998 — ch.
Suppressing Random Walks in Markov Chain Monte Carlo Using Ordered Overrelaxation.
Learning in Graphical Models
Radford M. Neal
1997 J jnl
Factor Analysis Using Delta-Rule Wake-Sleep Learning.
Neural Comput.
Radford M. Neal, Peter Dayan
1996 J jnl
Sampling from multimodal distributions using tempered transitions.
Stat. Comput.
Radford M. Neal
1995 B conf
Arithmetic Coding Revisited.
Data Compression Conference
Alistair Moffat, Radford M. Neal, Ian H. Witten
1995 — —
Bayesian learning for neural networks.
Radford M. Neal
1995 J jnl
The Helmholtz machine.
Neural Comput.
Peter Dayan, Geoffrey E. Hinton, Radford M. Neal, Richard S. Zemel
1993 J jnl
Comments on 'A theoretical analysis of Monte Carlo algorithms for the simulation of Gibbs random field images'.
IEEE Trans. Inf. Theory
Radford M. Neal
1992 J jnl
Asymmetric Parallel Boltzmann Machines are Belief Networks.
Neural Comput.
Radford M. Neal
1992 — conf
Bayesian Learning via Stochastic Dynamics.
NIPS
Radford M. Neal
1992 J jnl
Connectionist Learning of Belief Networks.
Artif. Intell.
Radford M. Neal
1987 J jnl
Arithmetic Coding for Data Compression.
Commun. ACM
Ian H. Witten, Radford M. Neal, John G. Cleary
1983 J jnl
Jade: A Distributed Software Prototyping Environment.
ACM SIGOPS Oper. Syst. Rev.
Ian H. Witten, Graham M. Birtwistle, John G. Cleary, David R. Hill, Danny Levinson, Greg Lomow, Radford M. Neal, Murray Peterson, Brian W. Unger, Brian Wyvill