21 citations · 88 across the 14 of their papers we have counts for
8 papers · 1 filter
Unsupervised Constrained Community Detection via Self-Expressive Graph Neural Network
Sambaran Bandyopadhyay, Vishal Peter
Graph neural networks (GNNs) are able to achieve promising performance on multiple graph downstream tasks such as node classification and link prediction. Comparatively lesser work…
Integrating Network Embedding and Community Outlier Detection via Multiclass Graph Description
Sambaran Bandyopadhyay, Saley Vishal Vivek, M. N. Murty
Network (or graph) embedding is the task to map the nodes of a graph to a lower dimensional vector space, such that it preserves the graph properties and facilitates the downstream…
Line Hypergraph Convolution Network: Applying Graph Convolution for Hypergraphs
Sambaran Bandyopadhyay, Kishalay Das, M. Narasimha Murty
Network representation learning and node classification in graphs got significant attention due to the invent of different types graph neural networks. Graph convolution network (G…
Beyond Node Embedding: A Direct Unsupervised Edge Representation Framework for Homogeneous Networks
Sambaran Bandyopadhyay, Anirban Biswas, M. N. Murty +1
Network representation learning has traditionally been used to find lower dimensional vector representations of the nodes in a network. However, there are very important edge drive…
Outlier Aware Network Embedding for Attributed Networks
Sambaran Bandyopadhyay, Lokesh N, M. N. Murty
Attributed network embedding has received much interest from the research community as most of the networks come with some content in each node, which is also known as node attribu…
SaC2Vec: Information Network Representation with Structure and Content
Sambaran Bandyopadhyay, Harsh Kara, Anirban Biswas +1
Network representation learning (also known as information network embedding) has been the central piece of research in social and information network analysis for the last couple…
FSCNMF: Fusing Structure and Content via Non-negative Matrix Factorization for Embedding Information Networks
Sambaran Bandyopadhyay, Harsh Kara, Aswin Kannan +1
Analysis and visualization of an information network can be facilitated better using an appropriate embedding of the network. Network embedding learns a compact low-dimensional vec…
A Generic Axiomatic Characterization of Centrality Measures in Social Network
Sambaran Bandyopadhyay, M. Narasimha Murty, Ramasuri Narayanam
Centrality is an important notion in complex networks; it could be used to characterize how influential a node or an edge is in the network. It plays an important role in several o…