Learn how GraphRAG transforms unstructured text into structured data, revolutionizing AI retrieval with deeper insights and ...

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In this paper we propose a graph representation learning technique on weighted and dynamic graphs to predict the network capacity, that is the weights of connections/links between viewers/nodes. We ...

In this work, an accurate and efficient statistical cell timing library characterization framework is proposed based on heterogeneous graph attention network (HGAT) assisted with parasitic RC ...

The method has been derived by resorting to the graph-theoretic approach to process-network synthesis based on process graphs (P-graphs); it also resorts to the methodology established in our previous ...

The optimal and near-optimal enterprise-wide networks are designed, that is synthesized, for supplying feedstocks and distributing multiple products manufactured from these feedstocks in the process ...