Note :
1. Please click on the "Paper" to access the paper. Also, please refer to my Google Scholar Profile and Research Gate Profile
2. Classifications of Publications: Journal Publication | Conference Publication | Book Chapter | Best Paper Award
3. * : Both authors contributed equally; ^ : A student/doctoral fellow/mentee of Dr. Tanujit Chakraborty during the time of the work.
1. Please click on the "Paper" to access the paper. Also, please refer to my Google Scholar Profile and Research Gate Profile
2. Classifications of Publications: Journal Publication | Conference Publication | Book Chapter | Best Paper Award
3. * : Both authors contributed equally; ^ : A student/doctoral fellow/mentee of Dr. Tanujit Chakraborty during the time of the work.
List of Publications (Year-wise) :
2022 :
2021 :
2020 :
2019 :
2018 :
2022 :
- Chakraborty, T., Kamat, G.^, Chakraborty, A. K. (2022). Bayesian Neural Tree Models for Nonparametric Regression. Australian & New Zealand Journal of Statistics, Accepted. [Paper | Code]
- Chakraborty, T., Das, S., & Chattopadhyay, S. (2022). A New Method for Generalizing Burr and Related Distributions. Mathematica Slovaca, Vol. 72, pg. 241-264. [Paper | Code]
- Bhattacharyya, A*., Chakraborty, T.*, & Rai, S. N. (2022). Stochastic forecasting of COVID-19 daily new cases across countries with a novel hybrid time series model. Nonlinear Dynamics, Vol. 107, pg. 3025-3040. [Paper | Code]
- Chakraborty, T., Ghosh, I., Mahajan, T.^, Arora, T.^ (2022). Nowcasting of COVID-19 confirmed cases: Foundations, trends, and challenges. In Modeling, Control and Drug Development for COVID-19 Outbreak Prevention, Vol. 366, pg. 1023-1064, Springer Book Chapter, Cham. [Paper | Code]
- Panja, M., Chakraborty, T., Kumar, U. (2022). Data Dictionary. In Encyclopedia of Mathematical Geosciences, Springer, Cham, Accepted (Invited Book Chapter). [Paper | Code]
- Chakraborty, T., Kumar, U. (2022). Loss Functions. In Encyclopedia of Mathematical Geosciences, Springer, Cham, Accepted (Invited Book Chapter). [Paper | Code]
2021 :
- Chakraborty, T., Chakraborty, A. K., Biswas, M., Banerjee, S.^, & Bhattacharya, S.^ (2021). Unemployment Rate Forecasting: A Hybrid Approach. Computational Economics, Vol. 57, pg. 183-201. [Paper | Code]
- Ray, A.*, Chakraborty, T.*, & Ghosh, D. (2021). Optimized ensemble deep learning framework for scalable forecasting of dynamics containing extreme events. Chaos: An Interdisciplinary Journal of Nonlinear Science, Vol. 31, pg. 1-15. [Paper | Code]
- Chattopadhyay, S., Chakraborty, T., Ghosh, K., Das, A. K. (2021). Modified Lomax Model: A heavy-tailed distribution for fitting large-scale real-world complex networks. Social Network Analysis and Mining, Vol. 11, pg. 11-43. [Paper | Code]
- Ghosh, I., Chakraborty, T. (2021). An integrated deterministic-stochastic approach for forecasting the long-term trajectories of COVID-19. International Journal of Modeling, Simulation, and Scientific Computing, Vol. 12, pg. 1-15. [Paper | Code]
- Bhattacharyya, A., Pattnaik, M., Chattopadhyay, S., & Chakraborty, T. (2021). Theta Autoregressive Neural Network: A Hybrid Time Series Model for Pandemic Forecasting. In IEEE International Joint Conference on Neural Networks (IJCNN). [Paper | Code]
- Chattopadhyay, S., Chakraborty, T., Ghosh, K., Das, A. K. (2021). Uncovering patterns in heavy-tailed networks : A journey beyond scale-free. In ACM IKDD CODS-COMAD. [Paper | Code] (Best Paper Award Winner at ACM CODS-COMAD)
2020 :
- Chakraborty, T., Ghosh, I. (2020). Real-time forecasts and risk assessment of novel coronavirus (COVID-19) cases: A data-driven analysis. Chaos, Solitons & Fractals, Vol. 135, pg. 1-10. [Paper | Code]
- Chakraborty, T., Chakraborty, A. K. (2020). Hellinger Net : A Hybrid Imbalance Learning Model to Improve Software Defect Prediction. IEEE Transactions on Reliability, Vol. 70, pg. 481-494. [Paper | Code]
- Chakraborty, T., & Chattopadhyay, S., & Chakraborty, A. K. (2020). Radial basis neural tree model for improving waste recovery process in a paper industry. Applied Stochastic Models in Business and Industry, Vol. 36, pg. 49-61. [Paper | Code]
- Chakraborty, T., Chakraborty, A. K. (2020). Superensemble classifier for improving predictions in imbalanced data sets. Communications in Statistics - Case Studies and Data Analysis, Vol. 6, pg. 123-141. [Paper | Code]
2019 :
- Chakraborty, T., Chakraborty, A. K., & Murthy, C. A. (2019). A nonparametric ensemble binary classifier and its statistical properties. Statistics & Probability Letters, Vol. 149, pg. 16-23. [Paper | Code]
- Chakraborty, T., Chattopadhyay, S., & Ghosh, I. (2019). Forecasting dengue epidemics using a hybrid methodology. Physica A: Statistical Mechanics and its Applications, Vol. 527, pg. 1-8. [Paper | Code]
- Chakraborty, T., Chakraborty, A. K., & Mansoor, Z.^ (2019). A hybrid regression model for water quality prediction. OPSEARCH, Vol. 56, pg. 1167-1178. [Paper | Code]
- Chakraborty, T., Chakraborty, A. K., & Chattopadhyay, S. (2019). A novel distribution-free hybrid regression model for manufacturing process efficiency improvement. Journal of Computational and Applied Mathematics, Vol. 362, pg. 130-142. [Paper | Code] (Best Student Paper Award Winner at 52nd Annual Convention of ORSI, India)
2018 :
- Chakraborty, T., Chattopadhyay, S., & Chakraborty, A. K. (2018). A novel hybridization of classification trees and artificial neural networks for selection of students in a business school. OPSEARCH, Vol. 55, pg. 434-446. [Paper | Code] (B.G. Raghavendra Memorial Award Winner from ORSI, India)