ABSTRACT: Foot-and-Mouth Disease (FMD) remains a critical threat to global livestock industries, causing severe economic losses and trade restrictions. This paper proposes a novel application of ...
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 ...
Graphs provide a powerful tool for coping with the non-uniformity and irregularity of 3D meshes, enabling multi-scale representations of 3D data. However, many existing methods either neglect the ...
When we have a dynamo_output_graph from tlparse this can be a helpful reproducer for problems in AOTAutograd. However, Dynamo cannot reliably retrace the output graphs it generates. The biggest ...
Microsoft Corp. today is expanding its Fabric data platform with the addition of native graph database and geospatial mapping capabilities, saying the enhancements enhance Fabric’s capacity to power ...
Graphs are a ubiquitous data structure and a universal language for representing objects and complex interactions. They can model a wide range of real-world systems, such as social networks, chemical ...
Abstract: Graph classification is essential for understanding complex biological systems, where molecular structures and interactions are naturally represented as graphs. Traditional graph neural ...
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