| AMON: An open source architecture for online monitoring, statistical analysis, and forensics of multi-gigabit streams M Kallitsis, SA Stoev, S Bhattacharya, G Michailidis IEEE Journal on Selected Areas in Communications 34 (6), 1834-1848, 2016 | 34 | 2016 |
| Analysis of hybrid censored competing risks data S Bhattacharya, B Pradhan, D Kundu Statistics 48 (5), 1138-1154, 2014 | 24 | 2014 |
| Adaptive statistical detection of false data injection attacks in smart grids MG Kallitsis, S Bhattacharya, S Stoev, G Michailidis 2016 IEEE Global Conference on Signal and Information Processing (GlobalSIP …, 2016 | 22 | 2016 |
| Data-adaptive trimming of the Hill estimator and detection of outliers in the extremes of heavy-tailed data S Bhattacharya, M Kallitsis, S Stoev Electronic Journal of Statistics 13 (1), 1872-1925, 2019 | 19* | 2019 |
| Quantile regression neural networks: a bayesian approach SR Jantre, S Bhattacharya, T Maiti Journal of Statistical Theory and Practice 15 (3), 68, 2021 | 14 | 2021 |
| Statistical foundation of Variational Bayes neural networks S Bhattacharya, T Maiti Neural Networks 137, 151-173, 2021 | 11 | 2021 |
| Layer adaptive node selection in Bayesian neural networks: Statistical guarantees and implementation details S Jantre, S Bhattacharya, T Maiti Neural Networks 167, 309-330, 2023 | 10 | 2023 |
| Detection of false data injection attacks in smart grids based on forecasts MG Kallitsis, S Bhattacharya, G Michailidis 2018 IEEE International Conference on Communications, Control, and Computing …, 2018 | 9 | 2018 |
| Comprehensive study of variational Bayes classification for dense deep neural networks S Bhattacharya, Z Liu, T Maiti Statistics and Computing 34 (1), 17, 2024 | 4* | 2024 |
| Statistically valid variational bayes algorithm for ising model parameter estimation M Kim, S Bhattacharya, T Maiti Journal of Computational and Graphical Statistics 33 (1), 75-84, 2024 | 4* | 2024 |
| Black Box Variational Bayesian Model Averaging V Kejzlar, S Bhattacharya, M Son, T Maiti The American Statistician 77 (1), 85-96, 2023 | 4 | 2023 |
| Sequential bayesian neural subnetwork ensembles S Jantre, S Madireddy, S Bhattacharya, T Maiti, P Balaprakash arXiv preprint arXiv:2206.00794, 2022 | 4 | 2022 |
| Outlier detection based on extreme value theory and applications S Bhattacharya, F Kamper, J Beirlant Scandinavian Journal of Statistics 50 (3), 1466-1502, 2023 | 3* | 2023 |
| A fast and calibrated computer model emulator: an empirical Bayes approach V Kejzlar, M Son, S Bhattacharya, T Maiti Statistics and Computing 31 (4), 49, 2021 | 3 | 2021 |
| Variational Bayes Ensemble Learning Neural Networks With Compressed Feature Space Z Liu, S Bhattacharya, T Maiti IEEE Transactions on Neural Networks and Learning Systems, 2022 | 1 | 2022 |
| Inference on the endpoint of human lifespan and its inherent statistical difficulty: Discussion on the paper by Holger Rootzén and Dmitrii Zholud SA Stoev, S Bhattacharya Extremes 21 (3), 391-404, 2018 | 1 | 2018 |
| A comprehensive study of spike and slab shrinkage priors for structurally sparse Bayesian neural networks S Jantre, S Bhattacharya, T Maiti arXiv preprint arXiv:2308.09104, 2023 | | 2023 |
| Parameter calibration for beta-decay calculations T Li, M Son, V Kejzlar, W Nazarewicz, T Maiti, S Bhattacharya, S Giuliani Bulletin of the American Physical Society 67, 2022 | | 2022 |
| Outlier Identification in Spatio-Temporal Processes S Bhattacharya | | 2018 |
| M. ALIZADEH, SF BAGHERI, E. BALOUI JAMKHANEH and S. NADARAJAH Estimates of the PDF and the CDF of the exponentiated Weibull distribution.. 695 Z. TAN RB SILVA, GM CORDEIRO, D KUNDU, CCM PARAÍBA, CAR DINIZ, ... | | |
