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Anirban Bhattacharya
Researcher at Texas A&M University
Publications - 136
Citations - 2727
Anirban Bhattacharya is an academic researcher from Texas A&M University. The author has contributed to research in topics: Prior probability & Bayesian probability. The author has an hindex of 23, co-authored 104 publications receiving 2146 citations. Previous affiliations of Anirban Bhattacharya include Florida State University & University of Nottingham.
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Probabilistic community detection with unknown number of communities
TL;DR: A coherent probabilistic framework for simultaneous estimation of the number of communities and the community structure is proposed, adapting recently developed Bayesian nonparametric techniques to network models and developed concentration properties of nonlinear functions of Bernoulli random variables.
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Bayesian shrinkage
TL;DR: In this article, a new class of Dirichlet Laplace (DL) priors are proposed, which are optimal and lead to efficient posterior computation exploiting results from normalized random measure theory.
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Bayesian data integration and variable selection for pan-cancer survival prediction using protein expression data.
TL;DR: This paper develops translational models to identify major actionable proteins that are associated with clinical outcomes, like the survival time of patients, and develops Bayesian hierarchical survival models, which accommodate all the challenges mentioned here.
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Signal Adaptive Variable Selector for the Horseshoe Prior
Pallavi Ray,Anirban Bhattacharya +1 more
TL;DR: The Signal Adaptive Variable Selector (SAVS) as discussed by the authors performs variable selection as a post model-fitting exercise using continuous shrinkage priors such as the popular horseshoe prior.
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Estimation of the offspring mean in a controlled branching process with a random control function
TL;DR: Wei and Winnicki as discussed by the authors developed a weighted conditional least squares estimator of the offspring mean of the CBP and derived the asymptotic limit distribution of the estimator when the process is subcritical, critical and supercritical.