| 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 |
0.679 |
|
| 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 |
0.692 |
|
| 2020 |
Cleary E, Garbuno-Inigo A, Lan S, Schneider T, Stuart AM. Calibrate, Emulate, Sample Journal of Computational Physics. 109716. DOI: 10.1016/J.Jcp.2020.109716 |
0.334 |
|
| 2019 |
Lan S. Adaptive dimension reduction to accelerate infinite-dimensional geometric Markov Chain Monte Carlo Journal of Computational Physics. 392: 71-95. DOI: 10.1016/J.Jcp.2019.04.043 |
0.434 |
|
| 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 |
0.69 |
|
| 2017 |
Beskos A, Girolami MA, Lan S, Farrell PE, Stuart AM. Geometric MCMC for Infinite-Dimensional Inverse Problems Journal of Computational Physics. 335: 327-351. DOI: 10.1016/J.Jcp.2016.12.041 |
0.442 |
|
| 2017 |
Schneider T, Lan S, Stuart A, Teixeira J. Earth System Modeling 2.0: A Blueprint for Models That Learn From Observations and Targeted High-Resolution Simulations Geophysical Research Letters. 44: 12,396-12,417. DOI: 10.1002/2017Gl076101 |
0.305 |
|
| 2016 |
Karcher MD, Palacios JA, Lan S, Minin VN. phylodyn: an R package for phylodynamic simulation and inference. Molecular Ecology Resources. PMID 27801980 DOI: 10.1111/1755-0998.12630 |
0.404 |
|
| 2016 |
House T, Ford A, Lan S, Bilson S, Buckingham-Jeffery E, Girolami M. Bayesian uncertainty quantification for transmissibility of influenza, norovirus and Ebola using information geometry. Journal of the Royal Society, Interface / the Royal Society. 13. PMID 27558850 DOI: 10.1098/Rsif.2016.0279 |
0.329 |
|
| 2016 |
Lan S, Bui-Thanh T, Christie M, Girolami M. Emulation of higher-order tensors in manifold Monte Carlo methods for Bayesian Inverse Problems Journal of Computational Physics. 308: 81-101. DOI: 10.1016/J.Jcp.2015.12.032 |
0.45 |
|
| 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 |
0.664 |
|
| 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 |
0.634 |
|
| 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 |
0.614 |
|
| 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 |
0.68 |
|
| 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 |
0.633 |
|
| 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 |
0.646 |
|
| 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 |
0.614 |
|
| 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 |
0.681 |
|
| 2014 |
Lan S, Streets J, Shahbaba B. Wormhole Hamiltonian Monte Carlo Proceedings of the National Conference On Artificial Intelligence. 3: 1953-1959. |
0.313 |
|
| 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 |
0.672 |
|
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