Linear-Algebraic Results Associated with Antiferromagnetic Heisenberg Chains. - Man-Duen Choi; Jeffrey S. Rosenthal; Peter Rosenthal (SIAM J. Matrix Anal. Appl., 1993)

Convergence Rates for Markov Chains. - Jeffrey S. Rosenthal (SIAM Rev., 1995)

Analysis of the Gibbs sampler for a model related to James-Stein estimators. - Jeffrey S. Rosenthal (Stat. Comput., 1996)

A simulation approach to convergence rates for Markov chain Monte Carlo algorithms. - Mary Kathryn Cowles; Jeffrey S. Rosenthal (Stat. Comput., 1998)

Extension of Fill's perfect rejection sampling algorithm to general chains. - James Allen Fill; Motoya Machida; Duncan J. Murdoch; Jeffrey S. Rosenthal (Random Struct. Algorithms, 2000)

Efficient use of exact samples. - Duncan J. Murdoch; Jeffrey S. Rosenthal (Stat. Comput., 2000)

Finding authorities and hubs from link structures on the World Wide Web. - Allan Borodin; Gareth O. Roberts; Jeffrey S. Rosenthal; Panayiotis Tsaparas (WWW, 2001)

Introduction to mathematical systems theory. a behavioral approach [Book Review]. - Jeffrey S. Rosenthal (IEEE Trans. Autom. Control., 2002)

A case study in the meta-reasoning procedure ND. - James J. Lu; Jeffrey S. Rosenthal; Andrew E. Shaffer (J. Exp. Theor. Artif. Intell., 2003)

Achieving limiting distributions for Markov chains using back buttons. - Andrey Feuerverger; Jeffrey S. Rosenthal (Stat. Comput., 2004)

Link analysis ranking: algorithms, theory, and experiments. - Allan Borodin; Gareth O. Roberts; Jeffrey S. Rosenthal; Panayiotis Tsaparas (ACM Trans. Internet Techn., 2005)

AMCMC: An R interface for adaptive MCMC. - Jeffrey S. Rosenthal (Comput. Stat. Data Anal., 2007)

Towards optimal scaling of metropolis-coupled Markov chain Monte Carlo. - Yves F. Atchadé; Gareth O. Roberts; Jeffrey S. Rosenthal (Stat. Comput., 2011)

Decrypting classical cipher text using Markov chain Monte Carlo. - Jian Chen; Jeffrey S. Rosenthal (Stat. Comput., 2012)

The Containment Condition and Adapfail Algorithms. - Krzysztof Latuszynski; Jeffrey S. Rosenthal (J. Appl. Probab., 2014)

Complexity bounds for Markov chain Monte Carlo algorithms via diffusion limits. - Gareth O. Roberts; Jeffrey S. Rosenthal (J. Appl. Probab., 2016)

Automatically tuned general-purpose MCMC via new adaptive diagnostics. - Jinyoung Yang; Jeffrey S. Rosenthal (Comput. Stat., 2017)

Predicting University Students' Academic Success and Choice of Major using Random Forests. - Cédric Beaulac; Jeffrey S. Rosenthal (CoRR, 2018)

Handling Missing Values using Decision Trees with Branch-Exclusive Splits. - Cédric Beaulac; Jeffrey S. Rosenthal (CoRR, 2018)

A Deep Latent-Variable Model Application to Select Treatment Intensity in Survival Analysis. - Cédric Beaulac; Jeffrey S. Rosenthal; David Hodgson (CoRR, 2018)

Stochastic simulation of sequential game-theory voting models. - Jeffrey S. Rosenthal (Commun. Stat. Simul. Comput., 2018)

An evaluation of machine learning techniques to predict the outcome of children treated for Hodgkin-Lymphoma on the AHOD0031 trial. - Cédric Beaulac; Jeffrey S. Rosenthal; Qinglin Pei; Debra Friedman; Suzanne L. Wolden; David Hodgson (Appl. Artif. Intell., 2020)

Analysis of a high-resolution hand-written digits data set with writer characteristics. - Cédric Beaulac; Jeffrey S. Rosenthal (CoRR, 2020)

BEST: a decision tree algorithm that handles missing values. - Cédric Beaulac; Jeffrey S. Rosenthal (Comput. Stat., 2020)

Weight-preserving simulated tempering. - Nicholas G. Tawn; Gareth O. Roberts; Jeffrey S. Rosenthal (Stat. Comput., 2020)

Jump Markov chains and rejection-free Metropolis algorithms. - Jeffrey S. Rosenthal; Aki Dote; Keivan Dabiri; Hirotaka Tamura; Sigeng Chen; Ali Sheikholeslami (Comput. Stat., 2021)

Distinguishing luck from skill through statistical simulation: a case study. - Zhaoyu Guo; Irwin Khuu; Kevin Zhu; Jeffrey S. Rosenthal; Frederic Paik Schoenberg (Commun. Stat. Simul. Comput., 2022)

Skew brownian motion and complexity of the alps algorithm. - Gareth O. Roberts; Jeffrey S. Rosenthal; Nicholas G. Tawn (J. Appl. Probab., 2022)

Convergence rate bounds for iterative random functions using one-shot coupling. - Sabrina Sixta; Jeffrey S. Rosenthal (Stat. Comput., 2022)

Introducing a New High-Resolution Handwritten Digits Data Set with Writer Characteristics. - Cédric Beaulac; Jeffrey S. Rosenthal (SN Comput. Sci., 2023)

Optimization via Rejection-Free Partial Neighbor Search. - Sigeng Chen; Jeffrey S. Rosenthal; Aki Dote; Hirotaka Tamura; Ali Sheikholeslami (Stat. Comput., 2023)

Sampling by divergence minimization. - Ameer Dharamshi; Vivian Ngo; Jeffrey S. Rosenthal (Commun. Stat. Simul. Comput., 2024)

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

Sampling via Rejection-Free Partial Neighbor Search. - Sigeng Chen; Jeffrey S. Rosenthal; Aki Dote; Hirotaka Tamura; Ali Sheikholeslami (Commun. Stat. Simul. Comput., 2025)