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20092022
most citedAdaptive-Rate Compressive Sensing Using Side Information

48 citations · 126 across the 51 of their papers we have counts for

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Showing 2020Show all

14 papers · 1 filter

cs.CV2020

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…

cs.RO2020

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…

math.OC2020★ 1 cited

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…

math.PR2020

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…

stat.AP2020

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…

cs.GT2020

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…

math.ST2020

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…

math.ST2020★ 1 cited

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-…

math.ST2020★ 1 cited

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…

stat.AP2020

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…

math.ST2020★ 2 cited

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…

math.ST2020★ 1 cited

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…

math.ST2020★ 1 cited

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…

math.ST2020

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…