Explaining variational approximations JT Ormerod, MP Wand The American Statistician 64 (2), 140-153, 2010 | 509 | 2010 |
On semiparametric regression with O'Sullivan penalized splines MP Wand, JT Ormerod Australian & New Zealand Journal of Statistics 50 (2), 179-198, 2008 | 284* | 2008 |
Mean field variational Bayes for elaborate distributions MP Wand, JT Ormerod, SA Padoan, R Fruhwirth Bayesian Analysis 6 (4), 847-900, 2011 | 214 | 2011 |
scMerge leverages factor analysis, stable expression, and pseudoreplication to merge multiple single-cell RNA-seq datasets Y Lin, S Ghazanfar, KYX Wang, JA Gagnon-Bartsch, KK Lo, X Su, ZG Han, ... Proceedings of the National Academy of Sciences 116 (20), 9775-9784, 2019 | 150* | 2019 |
Gaussian variational approximate inference for generalized linear mixed models JT Ormerod, MP Wand Journal of Computational and Graphical Statistics 21 (1), 2-17, 2012 | 120 | 2012 |
Variational Bayesian inference for parametric and nonparametric regression with missing data C Faes, JT Ormerod, MP Wand Journal of the American Statistical Association 106 (495), 959-971, 2011 | 104 | 2011 |
Smatr:(Standardised) major axis estimation and testing routines D Warton, J Ormerod R package version 2, 1, 2007 | 102 | 2007 |
Variational approximations for generalized linear latent variable models FKC Hui, DI Warton, JT Ormerod, V Haapaniemi, S Taskinen Journal of Computational and Graphical Statistics 26 (1), 35-43, 2017 | 84 | 2017 |
A variational Bayes approach to variable selection JT Ormerod, C You, S Müller | 79 | 2017 |
Theory of Gaussian variational approximation for a Poisson mixed model P Hall, JT Ormerod, MP Wand Statistica Sinica, 369-389, 2011 | 72 | 2011 |
Mean field variational Bayes for continuous sparse signal shrinkage: pitfalls and remedies S Neville, J Ormerod, M Wand | 70 | 2012 |
Penalized wavelets: embedding wavelets into semiparametric regression MP Wand, JT Ormerod Electronic Journal of Statistics 5, 1654-1717, 2011 | 61 | 2011 |
On variational Bayes estimation and variational information criteria for linear regression models C You, JT Ormerod, S Mueller Australian & New Zealand Journal of Statistics 56 (1), 73-87, 2014 | 53 | 2014 |
scDC: single cell differential composition analysis Y Cao, Y Lin, JT Ormerod, P Yang, JYH Yang, KK Lo BMC bioinformatics 20, 1-12, 2019 | 49 | 2019 |
AdaSampling for positive-unlabeled and label noise learning with bioinformatics applications P Yang, JT Ormerod, W Liu, C Ma, AY Zomaya, JYH Yang IEEE transactions on cybernetics 49 (5), 1932-1943, 2019 | 46 | 2019 |
Mean field variational Bayesian inference for nonparametric regression with measurement error TH Pham, JT Ormerod, MP Wand Computational Statistics & Data Analysis 68, 375-387, 2013 | 38 | 2013 |
Integrated single cell data analysis reveals cell specific networks and novel coactivation markers S Ghazanfar, AJ Bisogni, JT Ormerod, DM Lin, JYH Yang BMC systems biology 10, 11-24, 2016 | 29 | 2016 |
Mean field variational Bayesian inference for support vector machine classification J Luts, JT Ormerod Computational Statistics & Data Analysis 73, 163-176, 2014 | 25 | 2014 |
spicyR: Spatial analysis of in situ cytometry data in R EP Nicolas P Canete, Sourish S Iyengar, John T Ormerod, Heeva Baharlou ... Bioinformatics, 2022 | 23 | 2022 |
Skew-normal variational approximations for Bayesian inference JT Ormerod Unpublished article, 2011 | 22 | 2011 |