Tapabrata Maiti

According to our database, Tapabrata Maiti authored at least 28 papers between 2006 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2024

Comprehensive study of variational Bayes classification for dense deep neural networks.

Shrijita Bhattacharya, Zihuan Liu, Tapabrata Maiti

Stat. Comput., February, 2024

Variational Bayes Ensemble Learning Neural Networks With Compressed Feature Space.

Zihuan Liu, Shrijita Bhattacharya, Tapabrata Maiti

IEEE Trans. Neural Networks Learn. Syst., January, 2024

A Tensor Based Varying-Coefficient Model for Multi-Modal Neuroimaging Data Analysis.

Pratim Guha Niyogi, Martin A. Lindquist, Tapabrata Maiti

IEEE Trans. Signal Process., 2024

2023

Kernelized multiview signed graph learning for single-cell RNA sequencing data.

Abdullah Karaaslanli, Satabdi Saha, Tapabrata Maiti, Selin Aviyente

BMC Bioinform., December, 2023

Layer adaptive node selection in Bayesian neural networks: Statistical guarantees and implementation details.

Sanket R. Jantre, Shrijita Bhattacharya, Tapabrata Maiti

Neural Networks, October, 2023

Variational inference with vine copulas: an efficient approach for Bayesian computer model calibration.

Vojtech Kejzlar, Tapabrata Maiti

Stat. Comput., 2023

A comprehensive study of spike and slab shrinkage priors for structurally sparse Bayesian neural networks.

Sanket R. Jantre, Shrijita Bhattacharya, Tapabrata Maiti

CoRR, 2023

Multiple Signed Graph Learning for Gene Regulatory Network Inference.

Abdullah Karaaslanli, Satabdi Saha, Tapabrata Maiti, Selin Aviyente

Proceedings of the IEEE International Conference on Acoustics, 2023

2022

Coupled support tensor machine classification for multimodal neuroimaging data.

Peide Li, Seyyid Emre Sofuoglu, Selin Aviyente, Tapabrata Maiti

Stat. Anal. Data Min., 2022

Feature Selection integrated Deep Learning for Ultrahigh Dimensional and Highly Correlated Feature Space.

Arkaprabha Ganguli, Tapabrata Maiti

CoRR, 2022

Sequential Bayesian Neural Subnetwork Ensembles.

Sanket R. Jantre, Sandeep Madireddy, Shrijita Bhattacharya, Tapabrata Maiti, Prasanna Balaprakash

CoRR, 2022

scSGL: kernelized signed graph learning for single-cell gene regulatory network inference.

Abdullah Karaaslanli, Satabdi Saha, Selin Aviyente, Tapabrata Maiti

Bioinform., 2022

2021

A fast and calibrated computer model emulator: an empirical Bayes approach.

Vojtech Kejzlar, Mookyong Son, Shrijita Bhattacharya, Tapabrata Maiti

Stat. Comput., 2021

Statistical foundation of Variational Bayes neural networks.

Shrijita Bhattacharya, Tapabrata Maiti

Neural Networks, 2021

TEC: Tensor Ensemble Classifier for Big Data.

Peide Li, Rejaul Karim, Tapabrata Maiti

CoRR, 2021

2020

Statistical Aspects of High-Dimensional Sparse Artificial Neural Network Models.

Kaixu Yang, Tapabrata Maiti

Mach. Learn. Knowl. Extr., 2020

A Role for Prior Knowledge in Statistical Classification of the Transition from MCI to Alzheimer's Disease.

Zihuan Liu, Tapabrata Maiti, Andrew R. Bender

CoRR, 2020

Variational Bayes Neural Network: Posterior Consistency, Classification Accuracy and Computational Challenges.

Shrijita Bhattacharya, Zihuan Liu, Tapabrata Maiti

CoRR, 2020

2019

Patient-Specific Prediction of Abdominal Aortic Aneurysm Expansion Using Bayesian Calibration.

Liangliang Zhang, Zhenxiang Jiang, Jongeun Choi, Chae Young Lim, Tapabrata Maiti, Seungik Baek

IEEE J. Biomed. Health Informatics, 2019

Bayesian model selection for generalized linear models using non-local priors.

Guiling Shi, Chae Young Lim, Tapabrata Maiti

Comput. Stat. Data Anal., 2019

2016

Spatial regression and estimation of disease risks: A clustering-based approach.

Wenning Feng, Chae Young Lim, Tapabrata Maiti, Zhen Zhang

Stat. Anal. Data Min., 2016

2015

Appearance-based localization using Group LASSO regression with an indoor experiment.

Huan N. Do, Jongeun Choi, Chae Young Lim, Tapabrata Maiti

Proceedings of the IEEE International Conference on Advanced Intelligent Mechatronics, 2015

2013

Efficient Bayesian spatial prediction with mobile sensor networks using Gaussian Markov random fields.

Yunfei Xu, Jongeun Choi, Sarat C. Dass, Tapabrata Maiti

Autom., 2013

2012

Sequential Bayesian Prediction and Adaptive Sampling Algorithms for Mobile Sensor Networks.

Yunfei Xu, Jongeun Choi, Sarat C. Dass, Tapabrata Maiti

IEEE Trans. Autom. Control., 2012

A unified Bayesian approach for prediction and detection using mobile sensor networks.

Yunfei Xu, Jongeun Choi, Sarat C. Dass, Tapabrata Maiti

Proceedings of the 51th IEEE Conference on Decision and Control, 2012

2011

Horvitz-Thompson Estimator.

Tapabrata Maiti

Proceedings of the International Encyclopedia of Statistical Science, 2011

2009

An improved empirical bayes approach to estimating differential gene expression in microarray time-course data: BETR (Bayesian Estimation of Temporal Regulation).

Martin J. Aryee, José A. Gutiérrez-Pabello, Igor Kramnik, Tapabrata Maiti, John Quackenbush

BMC Bioinform., 2009

2006

Classification of pathological stage of prostate cancer patients using penalized splines.

Tathagata Banerjee, Tapabrata Maiti, Pushpal Mukhopadhyay

Comput. Stat. Data Anal., 2006