66 citations · 115 across the 26 of their papers we have counts for
8 papers · 1 filter
A Role for Prior Knowledge in Statistical Classification of the Transition from MCI to Alzheimer's Disease
Zihuan Liu, Tapabrate Maiti, Andrew R. Bender
The transition from mild cognitive impairment (MCI) to Alzheimer's disease (AD) is of great interest to clinical researchers. This phenomenon also serves as a valuable data source…
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…
Ultra high dimensional generalized additive model: Unified Theory and Methods
Kaixu Yang, Tapabrata Maiti
Generalized additive model is a powerful statistical learning and predictive modeling tool that has been applied in a wide range of applications. The need of high-dimensional addit…
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…