Tanujit Chakraborty
Cited by
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Real-time forecasts and risk assessment of novel coronavirus (COVID-19) cases: A data-driven analysis
T Chakraborty, I Ghosh
Chaos, Solitons & Fractals 135, 2020
Forecasting dengue epidemics using a hybrid methodology
T Chakraborty, S Chattopadhyay, I Ghosh
Physica A: Statistical Mechanics and its Applications 527, 2019
A novel hybridization of classification trees and artificial neural networks for selection of students in a business school
T Chakraborty, S Chattopadhyay, AK Chakraborty
Opsearch 55 (2), 434-446, 2018
A nonparametric ensemble binary classifier and its statistical properties
T Chakraborty, AK Chakraborty, CA Murthy
Statistics & Probability Letters 149, 16-23, 2019
A novel distribution-free hybrid regression model for manufacturing process efficiency improvement
T Chakraborty, AK Chakraborty, S Chattopadhyay
Journal of Computational and Applied Mathematics 362, 130-142, 2019
Unemployment rate forecasting: A hybrid approach
T Chakraborty, AK Chakraborty, M Biswas, S Banerjee, S Bhattacharya
Computational Economics 57, 183–201, 2020
A hybrid regression model for water quality prediction
T Chakraborty, AK Chakraborty, Z Mansoor
Opsearch 56 (4), 1167–1178, 2019
An integrated deterministic–stochastic approach for forecasting the long-term trajectories of COVID-19
I Ghosh, T Chakraborty
International Journal of Modeling, Simulation, and Scientific Computing, 2141001, 2021
Superensemble classifier for improving predictions in imbalanced datasets
T Chakraborty, AK Chakraborty
Communications in Statistics: Case Studies, Data Analysis and Applications 6 …, 2020
Hellinger net: A hybrid imbalance learning model to improve software defect prediction
T Chakraborty, AK Chakraborty
IEEE Transactions on Reliability, 2020
Radial basis neural tree model for improving waste recovery process in a paper industry
T Chakraborty, S Chattopadhyay, AK Chakraborty
Applied Stochastic Models in Business and Industry 36 (1), 49-61, 2020
Theta Autoregressive Neural Network: A Hybrid Time Series Model for Pandemic Forecasting
A Bhattacharyya, M Pattnaik, S Chattopadhyay, T Chakraborty
IEEE International Joint Conference on Neural Networks (IJCNN), 2021
Uncovering patterns in heavy-tailed networks: A journey beyond scale-free
S Chattopadhyay, T Chakraborty, K Ghosh, AK Das
ACM CODS-COMAD, 136-144, 2021
Modeling the Degree Distributions of Heavy-Tailed Networks by Generalized Lomax Models
T Chakraborty, S Chattopadhyay, S Das
Preprints, 2020
Bayesian neural tree models for nonparametric regression
T Chakraborty, G Kamat, AK Chakraborty
arXiv preprint arXiv:1909.00515, 2019
Imbalanced Ensemble Classifier for learning from imbalanced business school data set
T Chakraborty
International Journal of Mathematical, Engineering and Management Sciences 4 …, 2019
Modified Lomax Model: A heavy-tailed distribution for fitting large-scale real-world complex networks
S Chattopadhyay, T Chakraborty, K Ghosh, AK Das
Social Network Analysis and Mining 11 (1), 1-24, 2021
Stochastic forecasting of COVID-19 daily new cases across countries with a novel hybrid time series model
A Bhattacharyya, T Chakraborty, SN Rai
medRxiv, 2020.10. 01.20205021, 2021
A New Method for Generalizing Burr and Related Distributions
T Chakraborty, S Das, S Chattopadhyay
Mathematica Slovaca, 2021
Nowcasting of COVID-19 confirmed cases: Foundations, trends, and challenges
T Chakraborty, I Ghosh, T Mahajan, T Arora
Modeling, Control and Drug Development for COVID-19 Outbreak Prevention, 2021
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