Deborshee Sen

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David DunsonArts & Sciences Professor of Statistical Science & MathematicsEmail verificata su duke.edu
Ajay JasraProfessor of Data Science, The Chinese University of Hong Kong, ShenzhenEmail verificata su cuhk.edu.cn
Jianfeng Lu 鲁剑锋Department of Mathematics, Department of Chemistry and Department of Physics, Duke UniversityEmail verificata su math.duke.edu
Matthias SachsUniversity of Birmingham, School of MathematicsEmail verificata su bham.ac.uk
Sayan PatraDuke UniversityEmail verificata su duke.edu
Alexandre ThieryAssociate Professor, National University of Singapore (NUS)Email verificata su nus.edu.sg
Priyam DasAssistant ProfessorEmail verificata su vcu.edu
Theodore PapamarkouDistinguished professor, Zhejiang Normal UniversityEmail verificata su zjnu.edu.cn
Garritt L. PageBrigham Young UniversityEmail verificata su stat.byu.edu
Alexander L YoungUndergraduate Advisor, Department of Statistics, Harvard UniversityEmail verificata su fas.harvard.edu
Jue HouUniversity of Minnesota Twin CitiesEmail verificata su umn.edu
Zongqi XiaUniversity of PittsburghEmail verificata su post.harvard.edu
Edward CrippsAssociate Professor Statistics, University of Western AustraliaEmail verificata su uwa.edu.au
Lachlan AstfalckResearch Fellow, University of Western AustraliaEmail verificata su uwa.edu.au
Andrés F. BarrientosFlorida State University

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Deborshee Sen

Sr Data Scientist, Google

Email verificata su google.com - Home page

Causal Inference Monte Carlo methods Particle Filtering Bayesian Inference Neural networks


Titolo Ordina per citazioni Ordina per anno Ordina per titolo	Citata da Citata da	Anno
Posterior Projection for Inference in Constrained Spaces L Astfalck, D Sen, S Patra, E Cripps, D Dunson arXiv e-prints, arXiv: 1812.05741, 2018	35*	2018
On coupling particle filter trajectories D Sen, AH Thiery, A Jasra Statistics and Computing 28, 461-475, 2018	27	2018
Efficient posterior sampling for high-dimensional imbalanced logistic regression D Sen, M Sachs, J Lu, DB Dunson Biometrika 107 (4), 1005-1012, 2020	17	2020
Some contributions to sequential Monte Carlo methods for option pricing D Sen, A Jasra, Y Zhou Journal of Statistical Computation and Simulation 87 (4), 733-752, 2017	15	2017
Posterior computation with the Gibbs zig-zag sampler M Sachs, D Sen, J Lu, D Dunson Bayesian Analysis 18 (3), 909-927, 2023	10	2023
Bayesian inferences on uncertain ranks and orderings: Application to ranking players and lineups AF Barrientos, D Sen, GL Page, DB Dunson Bayesian Analysis 18 (3), 777-806, 2023	8	2023
Scalable Bayesian inference for time series via divide-and-conquer R Ou, D Sen, D Dunson arXiv preprint arXiv:2106.11043, 2021	8	2021
Clustering sequence data with mixture Markov chains with covariates using multiple simplex constrained optimization routine (MSiCOR) P Das, D Sen, D De, J Hou, ZSH Abad, N Kim, Z Xia, T Cai Journal of Computational and Graphical Statistics, 1-25, 2023	5*	2023
Bayesian neural networks and dimensionality reduction D Sen, T Papamarkou, D Dunson Handbook of Bayesian, Fiducial, and Frequentist Inference, 2024	4*	2024
Particle filter efficiency under limited communication D Sen Biometrika 109 (4), 921–935, 2022	3	2022
Targeted stochastic gradient Markov chain Monte Carlo for hidden Markov models with rare latent states R Ou, D Sen, AL Young, DB Dunson arXiv preprint arXiv:1810.13431, 2021	3*	2021

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