66 citations · 115 across the 26 of their papers we have counts for
28 papers
Co-Hub Node Based Multiview Graph Learning with Theoretical Guarantees
Bisakh Banerjee, Mohammad Alwardat, Tapabrata Maiti +1
Identifying the graphical structure underlying the observed multivariate data is essential in numerous applications. Current methodologies are predominantly confined to deducing a…
Robust Spatiotemporally Contiguous Anomaly Detection Using Tensor Decomposition
Rachita Mondal, Mert Indibi, Tapabrata Maiti +1
Anomaly detection in spatiotemporal data is a challenging problem encountered in a variety of applications, including video surveillance, medical imaging data, and urban traffic mo…
Signed Graph Learning: Algorithms and Theory
Abdullah Karaaslanli, Bisakh Banerjee, Tapabrata Maiti +1
Real-world data is often represented through the relationships between data samples, forming a graph structure. In many applications, it is necessary to learn this graph structure…
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…
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…
Error Controlled Feature Selection for Ultrahigh Dimensional and Highly Correlated Feature Space Using Deep Learning
Arkaprabha Ganguli, David Todem, Tapabrata Maiti
In recent years, deep learning has been at the center of analytics due to its impressive empirical success in analyzing complex data objects. Despite this success, most of the exis…