Knowledge-based semidefinite linear programming classifiers. - Vaithilingam Jeyakumar; John T. Ormerod; Robert S. Womersley (Optim. Methods Softw., 2006)

Penalised spline support vector classifiers: computational issues. - John T. Ormerod; Matthew P. Wand; Inge Koch (Comput. Stat., 2008)

Parsimonious Classification Via Generalized Linear Mixed Models. - Göran Kauermann; John T. Ormerod; Matthew P. Wand (J. Classif., 2010)

Grid based variational approximations. - John T. Ormerod (Comput. Stat. Data Anal., 2011)

Modelling Inverse Gaussian Data with Censored Response Values: EM versus MCMC. - Ross Stewart Sparks; Gordon J. Sutton; Peter J. Toscas; John T. Ormerod (Adv. Decis. Sci., 2011)

Comment. - John T. Ormerod; Matthew P. Wand (Technometrics, 2012)

Mean field variational Bayesian inference for nonparametric regression with measurement error. - Tung H. Pham; John T. Ormerod; Matthew P. Wand (Comput. Stat. Data Anal., 2013)

Mean field variational Bayesian inference for support vector machine classification. - Jan Luts; John T. Ormerod (Comput. Stat. Data Anal., 2014)

ClassifyR: an R package for performance assessment of classification with applications to transcriptomics. - Dario Strbenac; Graham J. Mann; John T. Ormerod; Jean Yee Hwa Yang (Bioinform., 2015)

Integrated single cell data analysis reveals cell specific networks and novel coactivation markers. - Shila Ghazanfar; Adam J. Bisogni; John T. Ormerod; David M. Lin; Jean Yee Hwa Yang (BMC Syst. Biol., 2016)

Wavelet-based gradient boosting. - Eugene Dubossarsky; Jerome H. Friedman; John T. Ormerod; Matthew P. Wand (Stat. Comput., 2016)

On generalized degrees of freedom with application in linear mixed models selection. - Chong You; Samuel Müller 001; John T. Ormerod (Stat. Comput., 2016)

Diagonal Discriminant Analysis with Feature Selection for High Dimensional Data. - Sarah Elizabeth Romanes; John Thomas Ormerod; Jean Yee Hwa Yang (CoRR, 2018)

DCARS: differential correlation across ranked samples. - Shila Ghazanfar; Dario Strbenac; John T. Ormerod; Jean Yee Hwa Yang; Ellis Patrick (Bioinform., 2019)

scDC: single cell differential composition analysis. - Yue Cao; Yingxin Lin; John T. Ormerod; Pengyi Yang; Jean Yee Hwa Yang; Kitty K. Lo (BMC Bioinform., 2019)

AdaSampling for Positive-Unlabeled and Label Noise Learning With Bioinformatics Applications. - Pengyi Yang; John T. Ormerod; Wei Liu 007; Chendong Ma; Albert Y. Zomaya; Jean Yee Hwa Yang (IEEE Trans. Cybern., 2019)

Variational nonparametric discriminant analysis. - Weichang Yu 001; Lamiae Azizi; John T. Ormerod (Comput. Stat. Data Anal., 2020)

Variational discriminant analysis with variable selection. - Weichang Yu 001; John T. Ormerod; Michael Stewart (Stat. Comput., 2020)

spicyR: spatial analysis of in situ cytometry data in R. - Nicolas P. Canete; Sourish S. Iyengar; John T. Ormerod; Heeva Baharlou; Andrew N. Harman; Ellis Patrick (Bioinform., 2022)

An Approximated Collapsed Variational Bayes Approach to Variable Selection in Linear Regression. - Chong You; John T. Ormerod; Xiangyang Li; Cheng Heng Pang; Xiao-Hua Zhou (J. Comput. Graph. Stat., 2023)

Fast Expectation Propagation for Heteroscedastic, Lasso-Penalized, and Quantile Regression. - Jackson Zhou; John T. Ormerod; Clara Grazian (J. Mach. Learn. Res., 2023)