Year |
Citation |
Score |
2020 |
Lan S, Holbrook A, Elias GA, Fortin NJ, Ombao H, Shahbaba B. Flexible Bayesian Dynamic Modeling of Correlation and Covariance Matrices. Bayesian Analysis. 15: 1199-1228. PMID 33868547 DOI: 10.1214/19-ba1173 |
0.55 |
|
2020 |
Gao X, Shen W, Shahbaba B, Fortin NJ, Ombao H. Evolutionary State-Space Model and Its Application to Time-Frequency Analysis of Local Field Potentials. Statistica Sinica. 30: 1561-1582. PMID 32774073 DOI: 10.5705/Ss.202017.0420 |
0.349 |
|
2020 |
Lan S, Holbrook A, Elias GA, Fortin NJ, Ombao H, Shahbaba B. Flexible Bayesian Dynamic Modeling of Correlation and Covariance Matrices Bayesian Analysis. 15: 1199-1228. DOI: 10.1214/19-Ba1173 |
0.586 |
|
2019 |
Li L, Holbrook A, Shahbaba B, Baldi P. Neural network gradient Hamiltonian Monte Carlo. Computational Statistics. 34: 281-299. PMID 31695242 DOI: 10.1007/S00180-018-00861-Z |
0.402 |
|
2018 |
Holbrook A, Lan S, Vandenberg-Rodes A, Shahbaba B. Geodesic Lagrangian Monte Carlo over the space of positive definite matrices: with application to Bayesian spectral density estimation. Journal of Statistical Computation and Simulation. 88: 982-1002. PMID 31105358 DOI: 10.1080/00949655.2017.1416470 |
0.577 |
|
2018 |
Zhang C, Shahbaba B, Zhao H. Variational Hamiltonian Monte Carlo via Score Matching Bayesian Analysis. 13: 485-506. DOI: 10.1214/17-Ba1060 |
0.422 |
|
2018 |
Gao X, Shahbaba B, Ombao H. Modeling Binary Time Series Using Gaussian Processes with Application to Predicting Sleep States Journal of Classification. 35: 549-579. DOI: 10.1007/S00357-018-9268-8 |
0.329 |
|
2017 |
Zhang C, Shahbaba B, Zhao H. Variational Hamiltonian Monte Carlo via Score Matching. Bayesian Analysis. 13: 485-506. PMID 37151569 DOI: 10.1214/17-ba1060 |
0.328 |
|
2017 |
Zhang C, Shahbaba B, Zhao H. Hamiltonian Monte Carlo acceleration using surrogate functions with random bases. Statistics and Computing. 27: 1473-1490. PMID 28983154 DOI: 10.1007/S11222-016-9699-1 |
0.438 |
|
2016 |
Albitar M, Shahbaba B, Agersborg S, Chang R, Albitar A, Uyeji D, Luchetta G, Su H, Zhang H. Development and Validation of Automated Flow Cytometry System for the Diagnosis and Prediction of Molecular Abnormalities in Myelodysplastic Syndrome Blood. 128: 1977-1977. DOI: 10.1182/Blood.V128.22.1977.1977 |
0.314 |
|
2016 |
Zhang C, Shahbaba B, Zhao H. Precomputing strategy for Hamiltonian Monte Carlo method based on regularity in parameter space Computational Statistics. 32: 253-279. DOI: 10.1007/S00180-016-0683-1 |
0.402 |
|
2016 |
Vandenberg-Rodes A, Moftakhari HR, AghaKouchak A, Shahbaba B, Sanders BF, Matthew RA. Projecting nuisance flooding in a warming climate using generalized linear models and Gaussian processes Journal of Geophysical Research: Oceans. 121: 8008-8020. DOI: 10.1002/2016Jc012084 |
0.318 |
|
2015 |
Lan S, Stathopoulos V, Shahbaba B, Girolami M. Markov Chain Monte Carlo from Lagrangian Dynamics. Journal of Computational and Graphical Statistics : a Joint Publication of American Statistical Association, Institute of Mathematical Statistics, Interface Foundation of North America. 24: 357-378. PMID 26240515 DOI: 10.1080/10618600.2014.902764 |
0.551 |
|
2015 |
Lan S, Palacios JA, Karcher M, Minin VN, Shahbaba B. An Efficient Bayesian Inference Framework for Coalescent-Based Nonparametric Phylodynamics. Bioinformatics (Oxford, England). PMID 26093147 DOI: 10.1093/Bioinformatics/Btv378 |
0.525 |
|
2015 |
Lan S, Stathopoulos V, Shahbaba B, Girolami M. Markov Chain Monte Carlo from Lagrangian Dynamics Journal of Computational and Graphical Statistics. 24: 357-378. DOI: 10.1080/10618600.2014.902764 |
0.458 |
|
2014 |
Lan S, Zhou B, Shahbaba B. Spherical Hamiltonian Monte Carlo for Constrained Target Distributions. Jmlr Workshop and Conference Proceedings. 32: 629-637. PMID 25914759 |
0.55 |
|
2014 |
Lan S, Streets J, Shahbaba B. Wormhole Hamiltonian Monte Carlo. Proceedings of the ... Aaai Conference On Artificial Intelligence. Aaai Conference On Artificial Intelligence. 2014: 1953-1959. PMID 25861551 |
0.492 |
|
2014 |
Shahbaba B, Zhou B, Lan S, Ombao H, Moorman D, Behseta S. A semiparametric Bayesian model for detecting synchrony among multiple neurons. Neural Computation. 26: 2025-51. PMID 24922500 DOI: 10.1162/Neco_A_00631 |
0.547 |
|
2014 |
Byrne S, Girolami M, Diaconis P, Seiler C, Holmes S, Dryden IL, Kent JT, Pereyra M, Shahbaba B, Lan S, Streets J, Simpson D. Discussion of the article ‘Geodesic Monte Carlo on Embedded Manifolds’ by Simon Byrne and Mark Girolami Scandinavian Journal of Statistics. 41: 1-2. DOI: 10.1111/Sjos.12081 |
0.498 |
|
2014 |
Shahbaba B, Lan S, Streets J. Contribution to the Discussion of the Paper ‘Geodesic Monte Carlo on Embedded Manifolds’ Scandinavian Journal of Statistics. 41: 14-15. DOI: 10.1111/Sjos.12065 |
0.569 |
|
2013 |
Zhou B, Konstorum A, Duong T, Tieu KH, Wells WM, Brown GG, Stern HS, Shahbaba B. A hierarchical modeling approach to data analysis and study design in a multi-site experimental fMRI study. Psychometrika. 78: 260-78. PMID 25107616 DOI: 10.1007/S11336-012-9298-9 |
0.31 |
|
2013 |
Shahbaba B, Johnson WO. Bayesian nonparametric variable selection as an exploratory tool for discovering differentially expressed genes. Statistics in Medicine. 32: 2114-26. PMID 23172736 DOI: 10.1002/Sim.5680 |
0.309 |
|
2013 |
Shahbaba B, Lan S, Johnson WO, Neal RM. Split Hamiltonian Monte Carlo Statistics and Computing. 24: 339-349. DOI: 10.1007/S11222-012-9373-1 |
0.557 |
|
2012 |
Shahbaba B, Shachaf CM, Yu Z. A pathway analysis method for genome-wide association studies. Statistics in Medicine. 31: 988-1000. PMID 22302470 DOI: 10.1002/Sim.4477 |
0.316 |
|
2009 |
Shahbaba B, Gentles AJ, Beyene J, Plevritis SK, Greenwood CMT. A Bayesian nonparametric method for model evaluation: Application to genetic studies Journal of Nonparametric Statistics. 21: 379-396. DOI: 10.1080/10485250802613558 |
0.383 |
|
2007 |
Shahbaba B, Neal RM. Improving classification when a class hierarchy is available using a hierarchy-based prior Bayesian Analysis. 2: 221-237. DOI: 10.1214/07-Ba209 |
0.335 |
|
2006 |
Shahbaba B, Neal RM. Gene function classification using Bayesian models with hierarchy-based priors. Bmc Bioinformatics. 7: 448. PMID 17038174 DOI: 10.1186/1471-2105-7-448 |
0.344 |
|
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