Jade: A Distributed Software Prototyping Environment. - 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 (ACM SIGOPS Oper. Syst. Rev., 1983)

Arithmetic Coding for Data Compression. - Ian H. Witten; Radford M. Neal; John G. Cleary (Commun. ACM, 1987)

Bayesian Learning via Stochastic Dynamics. - Radford M. Neal (NIPS, 1992)

Connectionist Learning of Belief Networks. - Radford M. Neal (Artif. Intell., 1992)

Asymmetric Parallel Boltzmann Machines are Belief Networks. - Radford M. Neal (Neural Comput., 1992)

Comments on 'A theoretical analysis of Monte Carlo algorithms for the simulation of Gibbs random field images'. - Radford M. Neal (IEEE Trans. Inf. Theory, 1993)

The Helmholtz machine. - Peter Dayan; Geoffrey E. Hinton; Radford M. Neal; Richard S. Zemel (Neural Comput., 1995)

Bayesian learning for neural networks. - Radford M. Neal (1995)

Sampling from multimodal distributions using tempered transitions. - Radford M. Neal (Stat. Comput., 1996)

Factor Analysis Using Delta-Rule Wake-Sleep Learning. - Radford M. Neal; Peter Dayan (Neural Comput., 1997)

Suppressing Random Walks in Markov Chain Monte Carlo Using Ordered Overrelaxation. - Radford M. Neal (Learning in Graphical Models, 1998)

A View of the Em Algorithm that Justifies Incremental, Sparse, and other Variants. - Radford M. Neal; Geoffrey E. Hinton (Learning in Graphical Models, 1998)

Arithmetic Coding Revisited. - Alistair Moffat; Radford M. Neal; Ian H. Witten (ACM Trans. Inf. Syst., 1998)

Inference for Belief Networks Using Coupling From the Past. - Michael Harvey; Radford M. Neal (UAI, 2000)

On Deducing Conditional Independence from d-Separation in Causal Graphs with Feedback (Research Note). - Radford M. Neal (J. Artif. Intell. Res., 2000)

Annealed importance sampling. - Radford M. Neal (Stat. Comput., 2001)

Inferring State Sequences for Non-linear Systems with Embedded Hidden Markov Models. - Radford M. Neal; Matthew J. Beal; Sam T. Roweis (NIPS, 2003)

Multiple Alignment of Continuous Time Series. - Jennifer Listgarten; Radford M. Neal; Sam T. Roweis; Andrew Emili (NIPS, 2004)

Classification with Bayesian Neural Networks. - Radford M. Neal (MLCW, 2005)

High Dimensional Classification with Bayesian Neural Networks and Dirichlet Diffusion Trees. - Radford M. Neal; Jianguo Zhang (Feature Extraction, 2006)

Bayesian Detection of Infrequent Differences in Sets of Time Series with Shared Structure. - Jennifer Listgarten; Radford M. Neal; Sam T. Roweis; Rachel Puckrin; Sean Cutler (NIPS, 2006)

Modeling Dyadic Data with Binary Latent Factors. - Edward Meeds; Zoubin Ghahramani; Radford M. Neal; Sam T. Roweis (NIPS, 2006)

Gene function classification using Bayesian models with hierarchy-based priors. - Babak Shahbaba; Radford M. Neal (BMC Bioinform., 2006)

Difference detection in LC-MS data for protein biomarker discovery. - Jennifer Listgarten; Radford M. Neal; Sam T. Roweis; Peter Wong; Andrew Emili (Bioinform., 2007)

Pattern Recognition and Machine Learning. - Radford M. Neal (Technometrics, 2007)

Nonlinear Models Using Dirichlet Process Mixtures. - Babak Shahbaba; Radford M. Neal (J. Mach. Learn. Res., 2009)

Gaussian Process Regression with Heteroscedastic or Non-Gaussian Residuals - Chunyi Wang; Radford M. Neal (CoRR, 2012)

Split Hamiltonian Monte Carlo. - Babak Shahbaba; Shiwei Lan; Wesley O. Johnson; Radford M. Neal (Stat. Comput., 2014)

Representing numeric data in 32 bits while preserving 64-bit precision. - Radford M. Neal (CoRR, 2015)

Fast exact summation using small and large superaccumulators. - Radford M. Neal (CoRR, 2015)

Non-reversibly updating a uniform [0, 1] value for Metropolis accept/reject decisions. - Radford M. Neal (CoRR, 2020)

Efficiency of reversible MCMC methods: elementary derivations and applications to composite methods. - Radford M. Neal; Jeffrey S. Rosenthal (J. Appl. Probab., 2025)