Marianne Menictas
Marianne Menictas
Postdoctoral Researcher, Harvard University
Verified email at - Homepage
Cited by
Cited by
Developments in mobile health just-in-time adaptive interventions for addiction science
SM Carpenter, M Menictas, I Nahum-Shani, DW Wetter, SA Murphy
Current addiction reports 7, 280-290, 2020
Sense2Stop: a micro-randomized trial using wearable sensors to optimize a just-in-time-adaptive stress management intervention for smoking relapse prevention
SL Battalio, DE Conroy, W Dempsey, P Liao, M Menictas, S Murphy, ...
Contemporary Clinical Trials 109, 106534, 2021
Variational inference for marginal longitudinal semiparametric regression
M Menictas, MP Wand
Stat 2 (1), 61-71, 2013
Streamlined variational inference with higher level random effects
TH Nolan, M Menictas, MP Wand
Journal of Machine Learning Research 21 (157), 1-62, 2020
Variational inference for heteroscedastic semiparametric regression
M Menictas, MP Wand
Australian & New Zealand Journal of Statistics 57 (1), 119-138, 2015
Artificial intelligence decision-making in mobile health
M Menictas, M Rabbi, P Klasnja, S Murphy
The biochemist 41 (5), 20-24, 2019
Streamlined variational inference for linear mixed models with crossed random effects
M Menictas, G Di Credico, MP Wand
Journal of Computational and Graphical Statistics 32 (1), 99-115, 2023
Streamlined variational inference for higher level group-specific curve models
M Menictas, TH Nolan, DG Simpson, MP Wand
Statistical Modelling 21 (6), 479-519, 2021
Optimal location of Tsunami warning buoys and sea level monitoring stations in the Mediterranean Sea
L Groen, A Joseph, E Black, M Menictas, W Tam, M Gabor
Science of Tsunami Hazards, 2010
Fast physical activity suggestions: Efficient hyperparameter learning in mobile health
M Menictas, S Tomkins, S Murphy
arXiv preprint arXiv:2012.11646, 2020
Variational inference for heteroscedastic and longitudinal regression models
M Menictas
Real-time Semiparametric Regression via Sequential Monte Carlo
M Menictas, CJ Oates, MP Wand
arXiv preprint arXiv:2310.12391, 2023
Streamlined Empirical Bayes Fitting of Linear Mixed Models in Mobile Health
M Menictas, S Tomkins, SA Murphy
arXiv preprint arXiv:2003.12881, 2020
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