48 citations · 126 across the 51 of their papers we have counts for
71 papers
A New Spatio-Temporal Model Exploiting Hamiltonian Equations
Satyaki Mazumder, Sayantan Banerjee, Sourabh Bhattacharya
The solutions of Hamiltonian equations are known to describe the underlying phase space of a mechanical system. In this article, we propose a novel spatio-temporal model using a st…
Additive Security Games: Structure and Optimization
Joe Clanin, Sourabh Bhattacharya
In this work, we provide a structural characterization of the possible Nash equilibria in the well-studied class of security games with additive utility. Our analysis yields a clas…
IID Sampling from Posterior Dirichlet Process Mixtures
Sourabh Bhattacharya
The influence of Dirichlet process mixture is ubiquitous in the Bayesian nonparametrics literature. But sampling from its posterior distribution remains a challenge, despite the ad…
IID Sampling from Doubly Intractable Distributions
Sourabh Bhattacharya
Intractable posterior distributions of parameters with intractable normalizing constants depending upon the parameters are known as doubly intractable posterior distributions. The…
IID Sampling from Intractable Multimodal and Variable-Dimensional Distributions
Sourabh Bhattacharya
Bhattacharya (2021b) has introduced a novel methodology for generating iid realizations from any target distribution on the Euclidean space, irrespective of dimensionality. In this…
IID Sampling from Intractable Distributions
Sourabh Bhattacharya
We propose a novel methodology for drawing iid realizations from any target distribution on the Euclidean space with arbitrary dimension. No assumption of compact support is necess…
Bayesian Levy-Dynamic Spatio-Temporal Process: Towards Big Data Analysis
Sourabh Bhattacharya
In this era of big data, all scientific disciplines are evolving fast to cope up with the enormity of the available information. So is statistics, the queen of science. Big data ar…
Deep Multi-view Image Fusion for Soybean Yield Estimation in Breeding Applications Deep Multi-view Image Fusion for Soybean Yield Estimation in Breeding Applications
Luis G Riera, Matthew E. Carroll, Zhisheng Zhang +8
Reliable seed yield estimation is an indispensable step in plant breeding programs geared towards cultivar development in major row crops. The objective of this study is to develop…
Planning for Aerial Robot Teams for Wide-Area Biometric and Phenotypic Data Collection
Tianshuang Gao, Shashwata Mandal, Sourabh Bhattacharya
This work presents an efficient and implementable solution to the problem of joint task allocation and path planning in a multi-UAV platform deployed for biometric data collection…
Function Optimization with Posterior Gaussian Derivative Process
Sucharita Roy, Sourabh Bhattacharya
We propose a Bayesian optimization algorithm for differentiable functions with available first and second partial derivatives. The objective function is modeled as a Gaussian proce…
Bayesian Appraisal of Random Series Convergence with Application to Climate Change
Sucharita Roy, Sourabh Bhattacharya
Roy and Bhattacharya (2020) provided Bayesian characterization of infinite series, and their most important application, namely, to the Dirichlet series characterizing the (in)famo…
How Ominous is the Premonition of Future Global Warming?
Debashis Chatterjee, Sourabh Bhattacharya
Global warming, the phenomenon of increasing global average temperature in the recent decades, is receiving wide attention due to its very significant adverse effects on climate. W…
On the Characterization of Saddle Point Equilibrium for Security Games with Additive Utility
HAmid Emadi, Sourabh Bhattacharya
In this work, we investigate a security game between an attacker and a defender, originally proposed in \cite{emadi2019security}. As is well known, the combinatorial nature of secu…
A Bayesian Multiple Testing Paradigm for Model Selection in Inverse Regression Problems
Debashis Chatterjee, Sourabh Bhattacharya
In this article, we propose a novel Bayesian multiple testing formulation for model and variable selection in inverse setups, judiciously embedding the idea of inverse reference di…
Convergence of Pseudo-Bayes Factors in Forward and Inverse Regression Problems
Debashis Chatterjee, Sourabh Bhattacharya
In the Bayesian literature on model comparison, Bayes factors play the leading role. In the classical statistical literature, model selection criteria are often devised used cross-…
Increasing Domain Infill Asymptotics for Stochastic Differential Equations Driven by Fractional Brownian Motion
Trisha Maitra, Sourabh Bhattacharya
Although statistical inference in stochastic differential equations (SDEs) driven by Wiener process has received significant attention in the literature, inference in those driven…
Hierarchical Bayesian state-space modeling of age- and sex-structured wildlife population dynamics
Sabyasachi Mukhopadhyay, Hans-Peter Piepho, Sourabh Bhattacharya +2
Biodiversity is declining at alarming rates worldwide, including for large wild mammals. It is therefore imperative to develop effective population conservation and recovery strate…
Posterior Consistency of Bayesian Inverse Regression and Inverse Reference Distributions
Debashis Chatterjee, Sourabh Bhattacharya
We consider Bayesian inference in inverse regression problems where the objective is to infer about unobserved covariates from observed responses and covariates. We establish poste…
Posterior Convergence of Nonparametric Binary and Poisson Regression Under Possible Misspecifications
Debashis Chatterjee, Sourabh Bhattacharya
In this article, we investigate posterior convergence of nonparametric binary and Poisson regression under possible model misspecification, assuming general stochastic process prio…
High-dimensional Asymptotic Theory of Bayesian Multiple Testing Procedures Under General Dependent Setup and Possible Misspecification
Noirrit Kiran Chandra, Sourabh Bhattacharya
In this article, we investigate the asymptotic properties of Bayesian multiple testing procedures under general dependent setup, when the sample size and the number of hypotheses b…
Bayesian Characterizations of Properties of Stochastic Processes with Applications
Sucharita Roy, Sourabh Bhattacharya
In this article, we primarily propose a novel Bayesian characterization of stationary and nonstationary stochastic processes. In practice, this theory aims to distinguish between g…
Posterior Convergence of Gaussian and General Stochastic Process Regression Under Possible Misspecifications
Debashis Chatterjee, Sourabh Bhattacharya
In this article, we investigate posterior convergence in nonparametric regression models where the unknown regression function is modeled by some appropriate stochastic process. In…
Bayes Factor Asymptotics for Variable Selection in the Gaussian Process Framework
Minerva Mukhopadhyay, Sourabh Bhattacharya
Although variable selection is one of the most popular areas of modern statistical research, much of its development has taken place in the classical paradigm compared to the Bayes…
Adaptive Target Tracking with a Mixed Team of Static and Mobile Guards: Deployment and Activation Strategies
Guillermo J. Laguna, Sourabh Bhattacharya
This work explores a variation of the art gallery problem in which a team of static and mobile guards track a mobile intruder with unknown maximum speed. First, we present an algor…