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Chapter and Conference Paper
LogE-Net: Logic Evolution Network for Temporal Knowledge Graph Forecasting
In recent years, research on predicting future events using temporal knowledge graphs by leveraging their rich structural and historical information has just begun. Due to their interesting application potenti...
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Chapter and Conference Paper
Exploring the Use of Dataflow Architectures for Graph Neural Network Workloads
Graph Neural Networks (GNNs), which learn representations of non-euclidean data, are rapidly rising in popularity and are used in several computationally demanding scientific applications. As these deep learni...