| 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 | 499 | 2020 |
| Forecasting dengue epidemics using a hybrid methodology T Chakraborty, S Chattopadhyay, I Ghosh Physica A: Statistical Mechanics and its Applications 527, 2019 | 121 | 2019 |
| Unemployment rate forecasting: A hybrid approach T Chakraborty, AK Chakraborty, M Biswas, S Banerjee, S Bhattacharya Computational Economics 57 (1), 183-201, 2021 | 86 | 2021 |
| Ten years of generative adversarial nets (GANs): a survey of the state-of-the-art T Chakraborty, UR KS, SM Naik, M Panja, B Manvitha Machine Learning: Science and Technology 5 (1), 1-35, 2024 | 70 | 2024 |
| Hellinger net: A hybrid imbalance learning model to improve software defect prediction T Chakraborty, AK Chakraborty IEEE Transactions on Reliability 70 (2), 481 - 494, 2020 | 48 | 2020 |
| 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 | 37 | 2018 |
| Optimized ensemble deep learning framework for scalable forecasting of dynamics containing extreme events A Ray, T Chakraborty, D Ghosh Chaos: An Interdisciplinary Journal of Nonlinear Science 31, 111105, 2021 | 35 | 2021 |
| W-Transformers: A Wavelet-based Transformer Framework for Univariate Time Series Forecasting L Sasal, T Chakraborty, A Hadid International Conference on Machine Learning and Applications, 2022 | 31 | 2022 |
| An ensemble neural network approach to forecast Dengue outbreak based on climatic condition M Panja, T Chakraborty, SS Nadim, I Ghosh, U Kumar, N Liu Chaos, Solitons & Fractals 167, 113124, 2023 | 29 | 2023 |
| 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 | 24 | 2019 |
| Stochastic forecasting of COVID-19 daily new cases across countries with a novel hybrid time series model A Bhattacharyya, T Chakraborty, SN Rai Nonlinear Dynamics 107, 3025–3040, 2022 | 22 | 2022 |
| 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 366, 2022 | 21 | 2022 |
| A nonparametric ensemble binary classifier and its statistical properties T Chakraborty, AK Chakraborty, CA Murthy Statistics & Probability Letters 149, 16-23, 2019 | 20 | 2019 |
| Epicasting: An ensemble wavelet neural network (ewnet) for forecasting epidemics M Panja, T Chakraborty, U Kumar, N Liu Neural Networks 165, 185-212, 2023 | 18 | 2023 |
| When Geoscience Meets Generative AI and Large Language Models: Foundations, Trends, and Future Challenges A Hadid, T Chakraborty, D Busby Expert Systems 41 (10), 1-16, 2024 | 17 | 2024 |
| A hybrid regression model for water quality prediction T Chakraborty, AK Chakraborty, Z Mansoor Opsearch 56, 1167-1178, 2019 | 17 | 2019 |
| Theta Autoregressive Neural Network: A Hybrid Time Series Model for Pandemic Forecasting A Bhattacharyya, S Chattopadhyay, M Pattnaik, T Chakraborty International Joint Conference on Neural Networks (IJCNN), 2021 | 14* | 2021 |
| Probabilistic AutoRegressive Neural Networks for Accurate Long-Range Forecasting M Panja, T Chakraborty, U Kumar, A Hadid International Conference on Neural Information Processing, 457-477, 2023 | 11* | 2023 |
| Superensemble classifier for improving predictions in imbalanced datasets T Chakraborty, AK Chakraborty Communications in Statistics: Case Studies, Data Analysis and Applications 6 …, 2020 | 11 | 2020 |
| Forecasting CPI inflation under economic policy and geopolitical uncertainties S Sengupta, T Chakraborty, SK Singh International Journal of Forecasting, 1-29, 2024 | 9 | 2024 |
