| Maternal cortisol over the course of pregnancy and subsequent child amygdala and hippocampus volumes and affective problems C Buss, EP Davis, B Shahbaba, JC Pruessner, K Head, CA Sandman Proceedings of the National Academy of Sciences 109 (20), E1312-E1319, 2012 | 662 | 2012 |
| Maternal psychosocial stress during pregnancy is associated with newborn leukocyte telomere length S Entringer, ES Epel, J Lin, C Buss, B Shahbaba, EH Blackburn, ... American journal of obstetrics and gynecology 208 (2), 134. e1-134. e7, 2013 | 271 | 2013 |
| Nonlinear models using Dirichlet process mixtures. B Shahbaba, R Neal Journal of Machine Learning Research 10 (8), 2009 | 270 | 2009 |
| Neural function, injury, and stroke subtype predict treatment gains after stroke E Burke Quinlan, L Dodakian, J See, A McKenzie, V Le, M Wojnowicz, ... Annals of neurology 77 (1), 132-145, 2015 | 203 | 2015 |
| Maternal exposure to childhood trauma is associated during pregnancy with placental-fetal stress physiology NK Moog, C Buss, S Entringer, B Shahbaba, DL Gillen, CJ Hobel, ... Biological psychiatry 79 (10), 831-839, 2016 | 128 | 2016 |
| Distributed stochastic gradient MCMC S Ahn, B Shahbaba, M Welling International conference on machine learning, 1044-1052, 2014 | 121 | 2014 |
| Genetic variation in the human brain dopamine system influences motor learning and its modulation by L-Dopa KM Pearson-Fuhrhop, B Minton, D Acevedo, B Shahbaba, SC Cramer PloS one 8 (4), e61197, 2013 | 107 | 2013 |
| Split hamiltonian monte carlo B Shahbaba, S Lan, WO Johnson, RM Neal Statistics and Computing 24, 339-349, 2014 | 98 | 2014 |
| What time is it? Deep learning approaches for circadian rhythms F Agostinelli, N Ceglia, B Shahbaba, P Sassone-Corsi, P Baldi Bioinformatics 32 (12), i8-i17, 2016 | 86 | 2016 |
| Wormhole hamiltonian monte carlo S Lan, J Streets, B Shahbaba Proceedings of the AAAI Conference on Artificial Intelligence 28 (1), 2014 | 83 | 2014 |
| A pluripotency signature predicts histologic transformation and influences survival in follicular lymphoma patients AJ Gentles, AA Alizadeh, SI Lee, JH Myklebust, CM Shachaf, B Shahbaba, ... Blood, The Journal of the American Society of Hematology 114 (15), 3158-3166, 2009 | 71 | 2009 |
| Spherical Hamiltonian Monte Carlo for constrained target distributions S Lan, B Zhou, B Shahbaba International Conference on Machine Learning, 629-637, 2014 | 67 | 2014 |
| Maternal folate concentration in early pregnancy and newborn telomere length S Entringer, ES Epel, J Lin, EH Blackburn, C Buss, B Shahbaba, DL Gillen, ... Annals of Nutrition and Metabolism 66 (4), 202-208, 2015 | 57 | 2015 |
| Improving classification when a class hierarchy is available using a hierarchy-based prior RM Neal, B Shahbaba | 48 | 2007 |
| Markov chain monte carlo from lagrangian dynamics S Lan, V Stathopoulos, B Shahbaba, M Girolami Journal of Computational and Graphical Statistics 24 (2), 357-378, 2015 | 47 | 2015 |
| Evolutionary state-space model and its application to time-frequency analysis of local field potentials X Gao, W Shen, B Shahbaba, NJ Fortin, H Ombao Statistica Sinica 30 (3), 1561, 2020 | 42 | 2020 |
| Gene function classification using Bayesian models with hierarchy-based priors B Shahbaba, RM Neal BMC bioinformatics 7 (1), 1-9, 2006 | 40 | 2006 |
| Hamiltonian Monte Carlo acceleration using surrogate functions with random bases C Zhang, B Shahbaba, H Zhao Statistics and computing 27, 1473-1490, 2017 | 38 | 2017 |
| An efficient Bayesian inference framework for coalescent-based nonparametric phylodynamics S Lan, JA Palacios, M Karcher, VN Minin, B Shahbaba Bioinformatics 31 (20), 3282-3289, 2015 | 35 | 2015 |
| Geodesic Lagrangian Monte Carlo over the space of positive definite matrices: with application to Bayesian spectral density estimation A Holbrook, S Lan, A Vandenberg-Rodes, B Shahbaba Journal of statistical computation and simulation 88 (5), 982-1002, 2018 | 34 | 2018 |
