66 citations · 115 across the 26 of their papers we have counts for
6 papers · 1 filter
A tensor based varying-coefficient model for multi-modal neuroimaging data analysis
Pratim Guha Niyogi, Martin A. Lindquist, Tapabrata Maiti
All neuroimaging modalities have their own strengths and limitations. A current trend is toward interdisciplinary approaches that use multiple imaging methods to overcome limitatio…
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…
ENNS: Variable Selection, Regression, Classification and Deep Neural Network for High-Dimensional Data
Kaixu Yang, Tapabrata Maiti
High-dimensional, low sample-size (HDLSS) data problems have been a topic of immense importance for the last couple of decades. There is a vast literature that proposed a wide vari…
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…
High Dimensional Classification for Spatially Dependent Data with Application to Neuroimaging
Yingjie Li, Liangliang Zhang, Tapabrata Maiti
Discriminating patients with Alzheimer's disease (AD) from healthy subjects is a crucial task in the research of Alzheimer's disease. The task can be potentially achieved by linear…
Uncertainty Estimation in Functional Linear Models
Tapabrata Maiti, Abolfazl Safikhani, Ping-Shou Zhong
Functional data analysis is proved to be useful in many scientific applications. The physical process is observed as curves and often there are several curves observed due to multi…