12 citations · 39 across the 11 of their papers we have counts for
13 papers
Spike-and-slab shrinkage priors for structurally sparse Bayesian neural networks
Sanket Jantre, Shrijita Bhattacharya, Tapabrata Maiti
Network complexity and computational efficiency have become increasingly significant aspects of deep learning. Sparse deep learning addresses these challenges by recovering a spars…
Sequential Bayesian Neural Subnetwork Ensembles
Sanket Jantre, Shrijita Bhattacharya, Nathan M. Urban +4
Deep ensembles have emerged as a powerful technique for improving predictive performance and enhancing model robustness across various applications by leveraging model diversity. H…
Variational Bayes algorithm and posterior consistency of Ising model parameter estimation
Minwoo Kim, Shrijita Bhattacharya, Tapabrata Maiti
Ising models originated in statistical physics and are widely used in modeling spatial data and computer vision problems. However, statistical inference of this model remains chall…
Layer Adaptive Node Selection in Bayesian Neural Networks: Statistical Guarantees and Implementation Details
Sanket Jantre, Shrijita Bhattacharya, Tapabrata Maiti
Sparse deep neural networks have proven to be efficient for predictive model building in large-scale studies. Although several works have studied theoretical and numerical properti…
Black Box Variational Bayesian Model Averaging
Vojtech Kejzlar, Shrijita Bhattacharya, Mookyong Son +1
For many decades now, Bayesian Model Averaging (BMA) has been a popular framework to systematically account for model uncertainty that arises in situations when multiple competing…
Variational Bayes Neural Network: Posterior Consistency, Classification Accuracy and Computational Challenges
Shrijita Bhattacharya, Zihuan Liu, Tapabrata Maiti
Bayesian neural network models (BNN) have re-surged in recent years due to the advancement of scalable computations and its utility in solving complex prediction problems in a wide…
Quantile Regression Neural Networks: A Bayesian Approach
Sanket R. Jantre, Shrijita Bhattacharya, Tapabrata Maiti
This article introduces a Bayesian neural network estimation method for quantile regression assuming an asymmetric Laplace distribution (ALD) for the response variable. It is shown…
A Fast and Calibrated Computer Model Emulator: An Empirical Bayes Approach
Vojtech Kejzlar, Mookyong Son, Shrijita Bhattacharya +1
Mathematical models implemented on a computer have become the driving force behind the acceleration of the cycle of scientific processes. This is because computer models are typica…
Statistical Foundation of Variational Bayes Neural Networks
Shrijita Bhattacharya, Tapabrata Maiti
Despite the popularism of Bayesian neural networks in recent years, its use is somewhat limited in complex and big data situations due to the computational cost associated with ful…
Outlier detection and a tail-adjusted boxplot based on extreme value theory
Shrijita Bhattacharya, Jan Beirlant
Whether an extreme observation is an outlier or not, depends strongly on the corresponding tail behaviour of the underlying distribution. We develop an automatic, data-driven metho…
Data-adaptive trimming of the Hill estimator and detection of outliers in the extremes of heavy-tailed data
Shrijita Bhattacharya, Michael Kallitsis, Stilian Stoev
We introduce a trimmed version of the Hill estimator for the index of a heavy-tailed distribution, which is robust to perturbations in the extreme order statistics. In the ideal Pa…
Trimming the Hill estimator: robustness, optimality and adaptivity
Shrijita Bhattacharya, Michael Kallitsis, Stilian Stoev
We introduce a trimmed version of the Hill estimator for the index of a heavy-tailed distribution, which is robust to perturbations in the extreme order statistics. In the ideal Pa…
AMON: An Open Source Architecture for Online Monitoring, Statistical Analysis and Forensics of Multi-gigabit Streams
Michael Kallitsis, Stilian Stoev, Shrijita Bhattacharya +1
The Internet, as a global system of interconnected networks, carries an extensive array of information resources and services. Key requirements include good quality-of-service and…