Swarup Chattopadhyay

Orcid: 0000-0003-3226-0416

According to our database1, Swarup Chattopadhyay authored at least 14 papers between 2014 and 2023.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

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PhD thesis 
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Links

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Bibliography

2023
SANGEET: A XML based Open Dataset for Research in Hindustani Sangeet.
CoRR, 2023

NeuroANATOP: An Effective Tool to Assess the Progression of Alzheimer's Disease in Human Brain Networks.
Proceedings of the IEEE International Conference on Knowledge Graph, 2023

Analyzing the Progression of Alzheimer's Disease in Human Brain Networks.
Proceedings of the International Conference on Advances in Social Networks Analysis and Mining, 2023

2022
Searching for Heavy-Tailed Probability Distributions for Modeling Real-World Complex Networks.
IEEE Access, 2022

2021
Modified Lomax model: a heavy-tailed distribution for fitting large-scale real-world complex networks.
Soc. Netw. Anal. Min., 2021

Node2vec with weak supervision on community structures.
Pattern Recognit. Lett., 2021

Towards effective discovery of natural communities in complex networks and implications in e-commerce.
Electron. Commer. Res., 2021

Theta Autoregressive Neural Network: A Hybrid Time Series Model for Pandemic Forecasting.
Proceedings of the International Joint Conference on Neural Networks, 2021

Uncovering patterns in heavy-tailed networks : A journey beyond scale-free.
Proceedings of the CODS-COMAD 2021: 8th ACM IKDD CODS and 26th COMAD, 2021

2020
Finding patterns in the degree distribution of real-world complex networks: going beyond power law.
Pattern Anal. Appl., 2020

Community Structure aware Embedding of Nodes in a Network.
CoRR, 2020

2019
A novel distribution-free hybrid regression model for manufacturing process efficiency improvement.
J. Comput. Appl. Math., 2019

2017
Generation of power-law networks by employing various attachment schemes: Structural properties emulating real world networks.
Inf. Sci., 2017

2014
Fitting truncated geometric distributions in large scale real world networks.
Theor. Comput. Sci., 2014


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