Sambaran Bandyopadhyay
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Outlier resistant unsupervised deep architectures for attributed network embedding
S Bandyopadhyay, L N, SV Vivek, MN Murty
Proceedings of the 13th international conference on web search and data …, 2020
Outlier aware network embedding for attributed networks
S Bandyopadhyay, N Lokesh, MN Murty
Proceedings of the AAAI conference on artificial intelligence 33 (01), 12-19, 2019
Data quality for machine learning tasks
N Gupta, S Mujumdar, H Patel, S Masuda, N Panwar, S Bandyopadhyay, ...
Proceedings of the 27th ACM SIGKDD conference on knowledge discovery & data …, 2021
Graph neural network to dilute outliers for refactoring monolith application
U Desai, S Bandyopadhyay, S Tamilselvam
Proceedings of the AAAI conference on artificial intelligence 35 (1), 72-80, 2021
Shopping queries dataset: A large-scale ESCI benchmark for improving product search
CK Reddy, L Màrquez, F Valero, N Rao, H Zaragoza, S Bandyopadhyay, ...
arXiv preprint arXiv:2206.06588, 2022
Voltage correlations in smart meter data
R Mitra, R Kota, S Bandyopadhyay, V Arya, B Sullivan, R Mueller, ...
Proceedings of the 21th ACM SIGKDD International Conference on Knowledge …, 2015
Hypergraph attention isomorphism network by learning line graph expansion
S Bandyopadhyay, K Das, MN Murty
2020 IEEE International Conference on Big Data (Big Data), 669-678, 2020
Individual and aggregate electrical load forecasting: One for all and all for one
S Bandyopadhyay, T Ganu, H Khadilkar, V Arya
Proceedings of the 2015 ACM Sixth International Conference on Future Energy …, 2015
Prevalence of brain injuries and recurrence of seizures in children with posttraumatic seizures
MK Badawy, PS Dayan, MG Tunik, FM Nadel, KA Lillis, M Miskin, ...
Academic emergency medicine 24 (5), 595-605, 2017
Fscnmf: Fusing structure and content via non-negative matrix factorization for embedding information networks
S Bandyopadhyay, H Kara, A Kannan, MN Murty
arXiv preprint arXiv:1804.05313, 2018
Beyond node embedding: a direct unsupervised edge representation framework for homogeneous networks
S Bandyopadhyay, A Biswas, MN Murty, R Narayanam
arXiv preprint arXiv:1912.05140, 2019
Monolith to Microservices: Representing Application Software through Heterogeneous Graph Neural Network.
A Mathai, S Bandyopadhyay, U Desai, S Tamilselvam
IJCAI, 3905-3911, 2022
A multilayered informative random walk for attributed social network embedding
S Bandyopadhyay, A Biswas, H Kara, MN Murty
ECAI 2020, 1738-1745, 2020
Gender differences in climate change perception and adaptation strategies: the case of three provinces in Vietnam’s Mekong River Delta
J McKinley, C Adaro, V Pede, P Rutsaert, T Setiyono, CT Thanh, ...
CCAFS Report, 2016
Dynamic structure learning through graph neural network for forecasting soil moisture in precision agriculture
A Vyas, S Bandyopadhyay
International Joint Conference on Artificial Intelligence, 2022
Unsupervised constrained community detection via self-expressive graph neural network
S Bandyopadhyay, V Peter
Uncertainty in Artificial Intelligence, 1078-1088, 2021
Planning curtailment of renewable generation in power grids
S Bandyopadhyay, P Kumar, V Arya
Proceedings of the International Conference on Automated Planning and …, 2016
A generic axiomatic characterization for measuring influence in social networks
S Bandyopadhyay, R Narayanam, MN Murty
2018 24th international conference on pattern recognition (icpr), 2606-2611, 2018
Detecting non-technical losses in electrical networks based on multi-layered statistical techniques from smart meter data
S Bandyopadhyay, Z Charbiwala, T Ganu, PDMIP Hj
US Patent 10,379,146, 2019
A machine learning based heating and cooling load forecasting approach for DHC networks
S Bandyopadhyay, J Hazra, S Kalyanaraman
IEEE Power and Energy Society Innovative Smart Grid Technologies Conference, 2018
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