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Sujayam Saha
Sujayam Saha
Verified email at berkeley.edu
Title
Cited by
Cited by
Year
On the nonparametric maximum likelihood estimator for Gaussian location mixture densities with application to Gaussian denoising
S Saha, A Guntuboyina
The Annals of Statistics 48 (2), 738-762, 2020
562020
Sharp Inequalities for -Divergences
A Guntuboyina, S Saha, G Schiebinger
IEEE transactions on information theory 60 (1), 104-121, 2013
492013
Two-component mixture model in the presence of covariates
N Deb, S Saha, A Guntuboyina, B Sen
Journal of the American Statistical Association 117 (540), 1820-1834, 2022
132022
Empirical Bayes mean estimation with nonparametric errors via order statistic regression on replicated data
N Ignatiadis, S Saha, DL Sun, O Muralidharan
Journal of the American Statistical Association 118 (542), 987-999, 2023
82023
Integrating binary traits with quantitative phenotypes for association mapping of multivariate phenotypes
I Mukhopadhyay, S Saha, S Ghosh
BMC proceedings 5, 1-4, 2011
42011
Intracranial recordings demonstrate both cortical and medial temporal lobe engagement in visual search in humans
SJK Slama, R Jimenez, S Saha, D King-Stephens, KD Laxer, PB Weber, ...
Journal of Cognitive Neuroscience 33 (9), 1833-1861, 2021
32021
Supplement to “On the nonparametric maximum likelihood estimator for Gaussian location mixture densities with application to Gaussian denoising.”
S Saha, A Guntuboyina
32020
Intracranial recordings demonstrate medial temporal lobe engagement in visual search in humans
SJK Slama, R Jimenez, S Saha, D King-Stephens, KD Laxer, PB Weber, ...
bioRxiv, 2020.02. 29.971341, 2020
12020
THE ANNALS
P Ao, EF ScHUsTIR, RC LITTELL
The Annals of Statistics 3 (4), 1975
11975
Package ‘NPMLEmix’
N Deb, S Saha, A Guntuboyina, B Sen, SR MOSEK, REB Rcpp
2020
Two-component Mixture Model in the Presence of Covariates—Supplement
N Deb, S Saha, A Guntuboyina, B Sen
2020
Information Theory, Dimension Reduction and Density Estimation
S Saha
University of California, Berkeley, 2018
2018
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