Automation of compressor test procedure using advantech data acquisition module. - Abdul Md. Mazid; Ryan Martin (ICARCV, 2008)

Lower Bounds for Identifying Codes in some Infinite Grids. - Ryan Martin; Brendon Stanton (Electron. J. Comb., 2010)

On epsilon-optimality of the pursuit learning algorithm - Ryan Martin; Omkar J. Tilak (CoRR, 2011)

ZFIN: enhancements and updates to the zebrafish model organism database. - Yvonne M. Bradford; Tom Conlin; Nathan A. Dunn; David Fashena; Ken Frazer; Douglas G. Howe; Jonathan Knight; Prita Mani; Ryan Martin; Sierra A. T. Moxon; Holly Paddock; Christian Pich 002; et al. (Nucleic Acids Res., 2011)

Decentralized Indirect Methods for Learning Automata Games. - Omkar J. Tilak; Ryan Martin; Snehasis Mukhopadhyay (IEEE Trans. Syst. Man Cybern. Part B, 2011)

On ε-Optimality of the Pursuit Learning Algorithm. - Ryan Martin; Omkar J. Tilak (J. Appl. Probab., 2012)

An Approximate Bayesian Marginal Likelihood Approach for Estimating Finite Mixtures. - Ryan Martin (Commun. Stat. Simul. Comput., 2013)

ZFIN, the Zebrafish Model Organism Database: increased support for mutants and transgenics. - Douglas G. Howe; Yvonne M. Bradford; Tom Conlin; Anne E. Eagle; David Fashena; Ken Frazer; Jonathan Knight; Prita Mani; Ryan Martin; Sierra A. T. Moxon; Holly Paddock; Christian Pich 002; et al. (Nucleic Acids Res., 2013)

Multilingual Search with Machine Translation in the Intel Communities. - Ryan Martin (AMTA (2), 2016)

A semiparametric scale-mixture regression model and predictive recursion maximum likelihood. - Ryan Martin; Zhen Han (Comput. Stat. Data Anal., 2016)

Prior-Free Probabilistic Prediction of Future Observations. - Ryan Martin; Rama T. Lingham (Technometrics, 2016)

Efficient simulation from a gamma distribution with small shape parameter. - Chuanhai Liu; Ryan Martin; Nicholas Syring (Comput. Stat., 2017)

Iterative refinement of implicit boundary models for improved geological feature reproduction. - Ryan Martin; Jeff B. Boisvert (Comput. Geosci., 2017)

The Zebrafish Model Organism Database: new support for human disease models, mutation details, gene expression phenotypes and searching. - Douglas G. Howe; Yvonne M. Bradford; Anne E. Eagle; David Fashena; Ken Frazer; Patrick Kalita; Prita Mani; Ryan Martin; Sierra Taylor Moxon; Holly Paddock; Christian Pich 002; Sridhar Ramachandran; et al. (Nucleic Acids Res., 2017)

Prior-Free Probabilistic Inference for Econometricians. - Ryan Martin (Robustness in Econometrics, 2017)

Towards justifying unsupervised stationary decisions for geostatistical modeling: Ensemble spatial and multivariate clustering with geomodeling specific clustering metrics. - Ryan Martin; Jeff B. Boisvert (Comput. Geosci., 2018)

Possibility Measures for Valid Statistical Inference Based on Censored Data. - Joyce Cahoon; Ryan Martin (ISIPTA, 2019)

Incorporating Expert Opinion in an Inferential Model while Maintaining Validity. - Leonardo Cella; Ryan Martin (ISIPTA, 2019)

On Valid Uncertainty Quantification About a Model. - Ryan Martin (ISIPTA, 2019)

Validity-Preservation Properties of Rules for Combining Inferential Models. - Ryan Martin; Nicholas Syring (ISIPTA, 2019)

Variational approximations using Fisher divergence. - Yue Yang; Ryan Martin; Howard D. Bondell (CoRR, 2019)

False confidence, non-additive beliefs, and valid statistical inference. - Ryan Martin (Int. J. Approx. Reason., 2019)

The Zebrafish Information Network: new support for non-coding genes, richer Gene Ontology annotations and the Alliance of Genome Resources. - Leyla Ruzicka; Douglas G. Howe; Sridhar Ramachandran; Sabrina Toro; Ceri E. Van Slyke; Yvonne M. Bradford; Anne E. Eagle; David Fashena; Ken Frazer; Patrick Kalita; Prita Mani; Ryan Martin; et al. (Nucleic Acids Res., 2019)

Ten Hot Topics around Scholarly Publishing. - Jonathan P. Tennant; Harry Crane; Tom Crick; Jacinto A. Dávila; Asura Enkhbayar; Johanna Havemann; Bianca Kramer; Ryan Martin; Paola Masuzzo; Andy Nobes; Curt Rice; Bárbara Rivera-López; et al. (Publ., 2019)

On an algorithm for solving Fredholm integrals of the first kind. - Minwoo Chae; Ryan Martin; Stephen G. Walker (Stat. Comput., 2019)

Performance of clustering for the decision of stationarity; A case study with a nickel laterite deposit. - Ryan Martin; Jeff B. Boisvert (Comput. Geosci., 2020)

Empirical Priors for Prediction in Sparse High-dimensional Linear Regression. - Ryan Martin; Yiqi Tang (J. Mach. Learn. Res., 2020)

Approximately Valid and Model-Free Possibilistic Inference. - Leonardo Cella; Ryan Martin (BELIEF, 2021)

Towards a Theory of Valid Inferential Models with Partial Prior Information. - Ryan Martin (BELIEF, 2021)

Stochastic Optimization for Numerical Evaluation of Imprecise Probabilities. - Nicholas Syring; Ryan Martin (ISIPTA, 2021)

Generalized inferential models for censored data. - Joyce Cahoon; Ryan Martin (Int. J. Approx. Reason., 2021)

The Zebrafish Information Network: major gene page and home page updates. - Douglas G. Howe; Sridhar Ramachandran; Yvonne M. Bradford; David Fashena; Sabrina Toro; Anne E. Eagle; Ken Frazer; Patrick Kalita; Prita Mani; Ryan Martin; Sierra Taylor Moxon; Holly Paddock; et al. (Nucleic Acids Res., 2021)

Valid Inferential Models Offer Performance and Probativeness Assurances. - Leonardo Cella; Ryan Martin (BELIEF, 2022)

A Practical Strategy for Valid Partial Prior-Dependent Possibilistic Inference. - Dominik Hose; Michael Hanss; Ryan Martin (BELIEF, 2022)

Validity, consonant plausibility measures, and conformal prediction. - Leonardo Cella; Ryan Martin (Int. J. Approx. Reason., 2022)

Valid inferential models for prediction in supervised learning problems. - Leonardo Cella; Ryan Martin (Int. J. Approx. Reason., 2022)

Direct and approximately valid probabilistic inference on a class of statistical functionals. - Leonardo Cella; Ryan Martin (Int. J. Approx. Reason., 2022)

Fiducial inference viewed through a possibility-theoretic inferential model lens. - Ryan Martin (ISIPTA, 2023)

A PRticle filter algorithm for nonparametric estimation of multivariate mixing distributions. - Vaidehi Dixit; Ryan Martin (Stat. Comput., 2023)

Possibility-theoretic statistical inference offers performance and probativeness assurances. - Leonardo Cella; Ryan Martin (Int. J. Approx. Reason., 2023)

Variational Approximations of Possibilistic Inferential Models. - Leonardo Cella; Ryan Martin (BELIEF, 2024)

Which Statistical Hypotheses are Afflicted with False Confidence? - Ryan Martin (BELIEF, 2024)

Large-Sample Theory for Inferential Models: A Possibilistic Bernstein-von Mises Theorem. - Ryan Martin; Jonathan P. Williams (BELIEF, 2024)

Decision-theoretic properties of possibilistic inferential models. - Ryan Martin (ISIPTA, 2025)

Computationally efficient variational-like approximations of possibilistic inferential models. - Leonardo Cella; Ryan Martin (Int. J. Approx. Reason., 2025)

Asymptotic efficiency of inferential models and a possibilistic Bernstein-von Mises theorem. - Ryan Martin; Jonathan P. Williams (Int. J. Approx. Reason., 2025)