no code implementations • 7 May 2021 • Stanislav Sobolevsky
This paper aims to connect the dots between the traditional Neural Network and the Graph Neural Network architectures as well as the network science approaches, harnessing the power of the hierarchical network organization.
1 code implementation • 3 Mar 2021 • Stanislav Sobolevsky
This paper proposes a new variant of the recurrent graph neural network algorithm for unsupervised network community detection through modularity optimization.
no code implementations • 25 Jan 2021 • Shivam Pathak, Mingyi He, Sergey Malinchik, Stanislav Sobolevsky
Digital sensing provides an unprecedented opportunity to assess and understand mobility.
no code implementations • 5 Dec 2019 • Urwa Muaz, Stanislav Sobolevsky
We propose use of an auxiliary classification task to extract features from unlabelled data by supervised learning, which can be used for unsupervised anomaly detection.
no code implementations • 22 Apr 2015 • Zolzaya Dashdorj, Stanislav Sobolevsky, Luciano Serafini, Fabrizio Antonelli, Carlo Ratti
This article addresses the issues in context awareness given heterogeneous and uncertain data of mobile network events missing reliable information on the context of this activity.