21 citations · 88 across the 14 of their papers we have counts for
6 papers · 1 filter
Dynamic Structure Learning through Graph Neural Network for Forecasting Soil Moisture in Precision Agriculture
Anoushka Vyas, Sambaran Bandyopadhyay
Soil moisture is an important component of precision agriculture as it directly impacts the growth and quality of vegetation. Forecasting soil moisture is essential to schedule the…
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…
Robust Hierarchical Graph Classification with Subgraph Attention
Sambaran Bandyopadhyay, Manasvi Aggarwal, M. Narasimha Murty
Graph neural networks get significant attention for graph representation and classification in machine learning community. Attention mechanism applied on the neighborhood of a node…
Unsupervised Graph Representation by Periphery and Hierarchical Information Maximization
Sambaran Bandyopadhyay, Manasvi Aggarwal, M. Narasimha Murty
Deep representation learning on non-Euclidean data types, such as graphs, has gained significant attention in recent years. Invent of graph neural networks has improved the state-o…
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…