Bayesian Analysis for Fault Location in Homogeneous Distributed Systems. - Yu Lo Cyrus Chang; Leslie C. Lander; Horng-Shing Lu; Martin T. Wells (SRDS, 1993)

Bayesian Normalization and Identification for Differential Gene Expression Data. - Dabao Zhang; Martin T. Wells; Christine D. Smart; William E. Fry (J. Comput. Biol., 2005)

Variable selection for large p small n regression models with incomplete data: Mapping QTL with epistases. - Min Zhang; Dabao Zhang; Martin T. Wells (BMC Bioinform., 2008)

The Exact Distribution of the Condition Number of a Gaussian Matrix. - William Anderson; Martin T. Wells (SIAM J. Matrix Anal. Appl., 2009)

Tree Space Prototypes: Another Look at Making Tree Ensembles Interpretable. - Hui Fen Tan; Giles Hooker; Martin T. Wells (CoRR, 2016)

Improved second order estimation in the singular multivariate normal model. - Didier Chételat; Martin T. Wells (J. Multivar. Anal., 2016)

Estimation of the inverse scatter matrix of an elliptically symmetric distribution. - Dominique Fourdrinier; Fatiha Mezoued; Martin T. Wells (J. Multivar. Anal., 2016)

On the domain of attraction of a Tracy-Widom law with applications to testing multiple largest roots. - Didier Chételat; Rajendran Narayanan; Martin T. Wells (J. Multivar. Anal., 2018)

Fairness criteria through the lens of directed acyclic graphical models. - Benjamin R. Baer; Daniel E. Gilbert; Martin T. Wells (CoRR, 2019)

Tree Space Prototypes: Another Look at Making Tree Ensembles Interpretable. - Sarah Tan; Matvey Soloviev; Giles Hooker; Martin T. Wells (FODS, 2020)

Robust Matrix Completion with Mixed Data Types. - Daqian Sun; Martin T. Wells (CoRR, 2020)

Hierarchical Adaptive Lasso: Learning Sparse Neural Networks with Shrinkage via Single Stage Training. - Skyler Seto; Martin T. Wells; Wenyu Zhang 003 (CoRR, 2020)

HALO: Learning to Prune Neural Networks with Shrinkage. - Skyler Seto; Martin T. Wells; Wenyu Zhang 003 (SDM, 2021)

A News-based Machine Learning Model for Adaptive Asset Pricing. - Liao Zhu; Haoxuan Wu; Martin T. Wells (CoRR, 2021)

Clustering Structure of Microstructure Measures. - Liao Zhu; Ningning Sun; Martin T. Wells (CoRR, 2021)

Interpretable Latent Variables in Deep State Space Models. - Haoxuan Wu; David S. Matteson; Martin T. Wells (CoRR, 2022)

On graphical models and convex geometry. - Haim Bar 001; Martin T. Wells (Comput. Stat. Data Anal., 2023)

Bellwether Trades: Characteristics of Trades influential in Predicting Future Price Movements in Markets. - Tejas Ramdas; Martin T. Wells (CoRR, 2024)

Robust estimation of the intrinsic dimension of data sets with quantum cognition machine learning. - Luca Candelori; Alexander G. Abanov; Jeffrey Berger; Cameron J. Hogan; Vahagn Kirakosyan; Kharen Musaelian; Ryan Samson; James E. T. Smith; Dario Villani; Martin T. Wells; Mengjia Xu (CoRR, 2024)

How Aligned are Generative Models to Humans in High-Stakes Decision-Making? - Sarah Tan; Keri Mallari; Julius Adebayo; Albert Gordo; Martin T. Wells; Kori Inkpen (CoRR, 2024)

Boltzmann convolutions and Welford mean-variance layers with an application to time series forecasting and classification. - Daniel Andrew Coulson; Martin T. Wells (CoRR, 2025)

Quantum Cognition Machine Learning for Forecasting Chromosomal Instability. - Giuseppe Di Caro; Vahagn Kirakosyan; Alexander G. Abanov; Luca Candelori; Nadine Hartmann; Ernest T. Lam; Kharen Musaelian; Ryan Samson; Dario Villani; Martin T. Wells; Richard J. Wenstrup; Mengjia Xu (CoRR, 2025)

Quantitative Relaxations of Arrow's Axioms. - Suvadip Sana; Daniel Brous; Martin T. Wells; Moon Duchin (CoRR, 2025)

Quantum Geometry of Data. - Alexander G. Abanov; Luca Candelori; Harold C. Steinacker; Martin T. Wells; Jerome R. Busemeyer; Cameron J. Hogan; Vahagn Kirakosyan; Nicola Marzari; Sunil Pinnamaneni; Dario Villani; Mengjia Xu; Kharen Musaelian (CoRR, 2025)