168 citations
Counting papers with at most 25 authors, so collaboration author lists do not stand in for the people here.
- Sorbonne UniversitéFR44 papers
- Centre National de la Recherche ScientifiqueFR27 papers
- Université Paris 1 Panthéon-SorbonneFR25 papers
- Laboratoire de Physique Théorique et Hautes EnergiesFR8 papers
- International Institute of Information Technology BangaloreIN6 papers
- National University of SingaporeSG5 papers
- Duke-NUS Medical SchoolSG4 papers
- Indian Statistical InstituteIN4 papers
- Institut d'Astrophysique de ParisFR4 papers
- Khalifa University of Science and TechnologyAE4 papers
- Université Paris-SaclayFR4 papers
- Université Paris Sciences et LettresFR4 papers
11 papers · 1 filter
Exact Algebraic Computation of Learning Coefficients for Two-Dimensional Singular Models
Grégoire Sergeant-Perthuis, Elias Tsigaridas, Jules Tsukahara
Classical information criteria such as the Bayesian Information Criterion (BIC) rely on regularity assumptions that break down for singular models, leading to incorrect model selec…
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…
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…
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…
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…
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…
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,…
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…
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…
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…
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…