Abstract: Graph neural networks (GNNs) have demonstrated outstanding performance in graph classification tasks. Most existing GNNs designed for graph classification adopt a structure that combines ...
Some shipowners have shied away from placing new orders in China this year, but overall appetite for building vessels in the country remains firm as build quality and legal risk improve. That is ...
Abstract: Graph classification is essential for understanding complex biological systems, where molecular structures and interactions are naturally represented as graphs. Traditional graph neural ...
A new study by researchers at Columbia University has revealed the states that have higher rates of arsenic in public drinking water systems, most of which are in the West and Midwest. Michigan, South ...
ABSTRACT: Enhancing the value of indigenous food crops such as Egusi melon, which is considered a “lost crop” in many places around the globe, can significantly contribute to food security of millions ...
TITLE: Determination of Organic Matter and Trace Metals Elements (As, Sb, Cd, Hg, Ni, Pb, Cr, Zn) in the Soils of the Banks of Watercourses in Brazzaville City (Republic of Congo) ...
Classic Graph Convolutional Networks (GCNs) often learn node representation holistically, which would ignore the distinct impacts from different neighbors when aggregating their features to update a ...
A federal judge has temporarily blocked President Donald Trump from restricting who is eligible for automatic US citizenship at birth, in an early legal setback for the new administration’s hard-line ...
While retrieval-augmented generation is effective for simpler queries, advanced reasoning questions require deeper connections between information that exist across documents. They require a knowledge ...
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