
COVID19 Knowledge Graph: Accelerating Information Retrieval and Discovery for Scientific Literature
The coronavirus disease (COVID19) has claimed the lives of over 350,000...
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PanRep: Universal node embeddings for heterogeneous graphs
Learning unsupervised node embeddings facilitates several downstream tas...
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Fewshot link prediction via graph neural networks for Covid19 drugrepurposing
Predicting interactions among heterogenous graph structured data has num...
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Tensor Graph Convolutional Networks for Multirelational and Robust Learning
The era of "data deluge" has sparked renewed interest in graphbased lea...
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Efficient and Stable Graph Scattering Transforms via Pruning
Graph convolutional networks (GCNs) have welldocumented performance in ...
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Edge Dithering for Robust Adaptive Graph Convolutional Networks
Graph convolutional networks (GCNs) are vulnerable to perturbations of t...
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GraphSAC: Detecting anomalies in largescale graphs
A graphbased sampling and consensus (GraphSAC) approach is introduced t...
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A Recurrent Graph Neural Network for MultiRelational Data
The era of data deluge has sparked the interest in graphbased learning ...
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Coupled Graphs and Tensor Factorization for Recommender Systems and Community Detection
Joint analysis of data from multiple information repositories facilitate...
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SemiBlind Inference of Topologies and Dynamical Processes over Graphs
Network science provides valuable insights across numerous disciplines i...
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Kernelbased Inference of Functions over Graphs
The study of networks has witnessed an explosive growth over the past de...
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Inference of SpatioTemporal Functions over Graphs via MultiKernel Kriged Kalman Filtering
Inference of spacetime varying signals on graphs emerges naturally in a...
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Vassilis N. Ioannidis
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