activity
20182026
most citedReal-time forecasts and risk assessment of novel coronavirus (COVID-19) cases: A data-driven analysis

403 citations · 936 across the 29 of their papers we have counts for

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Showing cs.LGShow all

13 papers · 1 filter

cs.LG2026

GraphSVR: A Graph Convolutional Support Vector Regression Framework for Robust Spatiotemporal Air Pollution Forecasting

Nourin Jahan, Muhammed Navas T, Tanujit Chakraborty +1

Urban air quality forecasting is challenging because pollutant concentrations are nonlinear, nonstationary, spatiotemporally dependent, and often affected by anomalous observations…

cs.LG2025★ 7 cited

Epidemic-guided deep learning for spatiotemporal forecasting of Tuberculosis outbreak

Madhab Barman, Madhurima Panja, Nachiketa Mishra +1

Tuberculosis (TB) remains a formidable global health challenge, driven by complex spatiotemporal transmission dynamics and influenced by factors such as population mobility and beh…

cs.LG2024★ 5 cited

Spatiotemporal Forecasting of Traffic Flow using Wavelet-based Temporal Attention

Yash Jakhmola, Madhurima Panja, Nitish Kumar Mishra +3

Spatiotemporal forecasting of traffic flow data represents a typical problem in the field of machine learning, impacting urban traffic management systems. In general, spatiotempora…

cs.LG2024★ 13 cited

WaveCatBoost for Probabilistic Forecasting of Regional Air Quality Data

Jintu Borah, Tanujit Chakraborty, Md. Shahrul Md. Nadzir +2

Accurate and reliable air quality forecasting is essential for protecting public health, sustainable development, pollution control, and enhanced urban planning. This letter presen…

cs.LG2024★ 3 cited

Survival modeling using deep learning, machine learning and statistical methods: A comparative analysis for predicting mortality after hospital admission

Ziwen Wang, Jin Wee Lee, Tanujit Chakraborty +5

Survival analysis is essential for studying time-to-event outcomes and providing a dynamic understanding of the probability of an event occurring over time. Various survival analys…

cs.LG2023★ 168 cited

Ten Years of Generative Adversarial Nets (GANs): A survey of the state-of-the-art

Tanujit Chakraborty, Ujjwal Reddy K S, Shraddha M. Naik +2

Since their inception in 2014, Generative Adversarial Networks (GANs) have rapidly emerged as powerful tools for generating realistic and diverse data across various domains, inclu…

cs.LG2023★ 13 cited

Prediction of Transportation Index for Urban Patterns in Small and Medium-sized Indian Cities using Hybrid RidgeGAN Model

Rahisha Thottolil, Uttam Kumar, Tanujit Chakraborty

The rapid urbanization trend in most developing countries including India is creating a plethora of civic concerns such as loss of green space, degradation of environmental health,…

cs.LG2022★ 44 cited

Knowledge-based Deep Learning for Modeling Chaotic Systems

Zakaria Elabid, Tanujit Chakraborty, Abdenour Hadid

Deep Learning has received increased attention due to its unbeatable success in many fields, such as computer vision, natural language processing, recommendation systems, and most…

cs.LG2022★ 44 cited

W-Transformers : A Wavelet-based Transformer Framework for Univariate Time Series Forecasting

Lena Sasal, Tanujit Chakraborty, Abdenour Hadid

Deep learning utilizing transformers has recently achieved a lot of success in many vital areas such as natural language processing, computer vision, anomaly detection, and recomme…

cs.LG2022★ 34 cited

Epicasting: An Ensemble Wavelet Neural Network (EWNet) for Forecasting Epidemics

Madhurima Panja, Tanujit Chakraborty, Uttam Kumar +1

Infectious diseases remain among the top contributors to human illness and death worldwide, among which many diseases produce epidemic waves of infection. The unavailability of spe…

cs.LG2021★ 33 cited

Optimized ensemble deep learning framework for scalable forecasting of dynamics containing extreme events

Arnob Ray, Tanujit Chakraborty, Dibakar Ghosh

The remarkable flexibility and adaptability of both deep learning models and ensemble methods have led to the proliferation for their application in understanding many physical phe…

cs.LG2018★ 3 cited

Superensemble Classifier for Improving Predictions in Imbalanced Datasets

Tanujit Chakraborty, Ashis Kumar Chakraborty

Learning from an imbalanced dataset is a tricky proposition. Because these datasets are biased towards one class, most existing classifiers tend not to perform well on minority cla…

cs.LG2018★ 4 cited

Imbalanced Ensemble Classifier for learning from imbalanced business school data set

Tanujit Chakraborty

Private business schools in India face a common problem of selecting quality students for their MBA programs to achieve the desired placement percentage. Generally, such data sets…