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Tapabrata Maiti
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2020 – today
- 2024
- [j20]Minwoo Kim
, Shrijita Bhattacharya, Tapabrata Maiti:
Statistically Valid Variational Bayes Algorithm for Ising Model Parameter Estimation. J. Comput. Graph. Stat. 33(1): 75-84 (2024) - [j19]Shrijita Bhattacharya, Zihuan Liu, Tapabrata Maiti:
Comprehensive study of variational Bayes classification for dense deep neural networks. Stat. Comput. 34(1): 17 (2024) - [j18]Arkaprabha Ganguli
Error-controlled feature selection for ultrahigh-dimensional and highly correlated feature space using deep learning. Stat. Anal. Data Min. 17(2) (2024) - [j17]Zihuan Liu
Variational Bayes Ensemble Learning Neural Networks With Compressed Feature Space. IEEE Trans. Neural Networks Learn. Syst. 35(1): 1379-1385 (2024) - [j16]Pratim Guha Niyogi
A Tensor Based Varying-Coefficient Model for Multi-Modal Neuroimaging Data Analysis. IEEE Trans. Signal Process. 72: 1607-1619 (2024) - 2023
- [j15]Abdullah Karaaslanli, Satabdi Saha, Tapabrata Maiti, Selin Aviyente:
Kernelized multiview signed graph learning for single-cell RNA sequencing data. BMC Bioinform. 24(1): 127 (2023) - [j14]Sanket R. Jantre
Layer adaptive node selection in Bayesian neural networks: Statistical guarantees and implementation details. Neural Networks 167: 309-330 (2023) - [j13]Vojtech Kejzlar
Variational inference with vine copulas: an efficient approach for Bayesian computer model calibration. Stat. Comput. 33(1): 18 (2023) - [c4]Abdullah Karaaslanli, Satabdi Saha, Tapabrata Maiti, Selin Aviyente:
Multiple Signed Graph Learning for Gene Regulatory Network Inference. ICASSP 2023: 1-5 - [i9]Sanket R. Jantre
A comprehensive study of spike and slab shrinkage priors for structurally sparse Bayesian neural networks. CoRR abs/2308.09104 (2023) - 2022
- [j12]Abdullah Karaaslanli
scSGL: kernelized signed graph learning for single-cell gene regulatory network inference. Bioinform. 38(11): 3011-3019 (2022) - [j11]Peide Li, Seyyid Emre Sofuoglu
Coupled support tensor machine classification for multimodal neuroimaging data. Stat. Anal. Data Min. 15(6): 797-818 (2022) - [i8]Peide Li, Seyyid Emre Sofuoglu, Tapabrata Maiti, Selin Aviyente:
Coupled Support Tensor Machine Classification for Multimodal Neuroimaging Data. CoRR abs/2201.07683 (2022) - [i7]Sanket R. Jantre
Sequential Bayesian Neural Subnetwork Ensembles. CoRR abs/2206.00794 (2022) - [i6]Arkaprabha Ganguli, Tapabrata Maiti:
Feature Selection integrated Deep Learning for Ultrahigh Dimensional and Highly Correlated Feature Space. CoRR abs/2209.07011 (2022) - 2021
- [j10]Shrijita Bhattacharya, Tapabrata Maiti:
Statistical foundation of Variational Bayes neural networks. Neural Networks 137: 151-173 (2021) - [j9]Vojtech Kejzlar
A fast and calibrated computer model emulator: an empirical Bayes approach. Stat. Comput. 31(4): 49 (2021) - [i5]Peide Li, Rejaul Karim, Tapabrata Maiti:
TEC: Tensor Ensemble Classifier for Big Data. CoRR abs/2103.00025 (2021) - [i4]Sanket R. Jantre, Shrijita Bhattacharya, Tapabrata Maiti:
Layer Adaptive Node Selection in Bayesian Neural Networks: Statistical Guarantees and Implementation Details. CoRR abs/2108.11000 (2021) - 2020
- [j8]Kaixu Yang
Statistical Aspects of High-Dimensional Sparse Artificial Neural Network Models. Mach. Learn. Knowl. Extr. 2(1): 1-19 (2020) - [i3]Shrijita Bhattacharya, Tapabrata Maiti:
Statistical Foundation of Variational Bayes Neural Networks. CoRR abs/2006.15786 (2020) - [i2]Shrijita Bhattacharya, Zihuan Liu, Tapabrata Maiti:
Variational Bayes Neural Network: Posterior Consistency, Classification Accuracy and Computational Challenges. CoRR abs/2011.09592 (2020) - [i1]Zihuan Liu, Tapabrata Maiti, Andrew R. Bender:
A Role for Prior Knowledge in Statistical Classification of the Transition from MCI to Alzheimer's Disease. CoRR abs/2012.00538 (2020)
2010 – 2019
- 2019
- [j7]Guiling Shi, Chae Young Lim
Bayesian model selection for generalized linear models using non-local priors. Comput. Stat. Data Anal. 133: 285-296 (2019) - [j6]Liangliang Zhang
Patient-Specific Prediction of Abdominal Aortic Aneurysm Expansion Using Bayesian Calibration. IEEE J. Biomed. Health Informatics 23(6): 2537-2550 (2019) - 2016
- [j5]Wenning Feng, Chae Young Lim, Tapabrata Maiti, Zhen Zhang
Spatial regression and estimation of disease risks: A clustering-based approach. Stat. Anal. Data Min. 9(6): 417-434 (2016) - 2015
- [c3]Huan N. Do, Jongeun Choi, Chae Young Lim, Tapabrata Maiti:
Appearance-based localization using Group LASSO regression with an indoor experiment. AIM 2015: 984-989 - 2013
- [j4]Yunfei Xu, Jongeun Choi
Efficient Bayesian spatial prediction with mobile sensor networks using Gaussian Markov random fields. Autom. 49(12): 3520-3530 (2013) - 2012
- [j3]Yunfei Xu, Jongeun Choi
Sequential Bayesian Prediction and Adaptive Sampling Algorithms for Mobile Sensor Networks. IEEE Trans. Autom. Control. 57(8): 2078-2084 (2012) - [c2]Yunfei Xu, Jongeun Choi
Efficient Bayesian spatial prediction with mobile sensor networks using Gaussian Markov random fields. ACC 2012: 2171-2176 - [c1]Yunfei Xu, Jongeun Choi
A unified Bayesian approach for prediction and detection using mobile sensor networks. CDC 2012: 1180-1185 - 2011
- [r1]Tapabrata Maiti:
Horvitz-Thompson Estimator. International Encyclopedia of Statistical Science 2011: 637-638
2000 – 2009
- 2009
- [j2]Martin J. Aryee, José A. Gutiérrez-Pabello, Igor Kramnik
An improved empirical bayes approach to estimating differential gene expression in microarray time-course data: BETR (Bayesian Estimation of Temporal Regulation). BMC Bioinform. 10: 409 (2009) - 2006
- [j1]Tathagata Banerjee, Tapabrata Maiti, Pushpal Mukhopadhyay:
Classification of pathological stage of prostate cancer patients using penalized splines. Comput. Stat. Data Anal. 51(2): 1147-1155 (2006)
Coauthor Index
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