The Discriminative Power of Non-Specific Laboratory Results. - Jacob P. VanHouten; Christopher Fonnesbeck; Michael E. Matheny; Thomas A. Lasko (AMIA, 2016)

Probabilistic programming in Python using PyMC3. - John Salvatier; Thomas V. Wiecki; Christopher Fonnesbeck (PeerJ Prepr., 2016)

A Bayesian Double Fusion Model for Resting-State Brain Connectivity Using Joint Functional and Structural Data. - Hakmook Kang; Hernando C. Ombao; Christopher Fonnesbeck; Zhaohua Ding; Victoria L. Morgan (Brain Connect., 2017)

Quantifying the Value of Perfect Information in Emergency Vaccination Campaigns. - Naomi V. Bradbury; William J. M. Probert; Katriona Shea; Michael C. Runge; Christopher Fonnesbeck; Matt J. Keeling; Matthew J. Ferrari; Michael J. Tildesley (PLoS Comput. Biol., 2017)

Real-time decision-making during emergency disease outbreaks. - William J. M. Probert; Chris P. Jewell; Marleen Werkman; Christopher Fonnesbeck; Yoshitaka Goto; Michael C. Runge; Satoshi Sekiguchi; Katriona Shea; Matt J. Keeling; Matthew J. Ferrari; Michael J. Tildesley (PLoS Comput. Biol., 2018)

A nonparametric updating method to correct clinical prediction model drift. - Sharon E. Davis; Robert A. Greevy Jr.; Christopher Fonnesbeck; Thomas A. Lasko; Colin G. Walsh; Michael E. Matheny (J. Am. Medical Informatics Assoc., 2019)

PyMC: a modern, and comprehensive probabilistic programming framework in Python. - Oriol Abril Pla; Virgile Andréani; Colin Carroll; Larry Dong; Christopher Fonnesbeck; Maxim Kochurov; Ravin Kumar; Junpeng Lao; Christian C. Luhmann; Osvaldo A. Martin; Michael Osthege; Ricardo Vieira; et al. (PeerJ Comput. Sci., 2023)