A comprehensive, production-ready implementation of Graph Isomorphism Networks (GIN) for graph classification tasks. This project provides a clean, reproducible, and showcase-ready implementation with ...
The Graph Isomorphism Problem is the computational problem of determining whether two finite graphs are isomorphic. I chose to represent the graphs using an adjacency matrix, this way I can easily ...
Abstract: The graph neural networks (GNNs) have drawn much attention for predicting the remaining useful life (RUL) due to their excellent performance in processing correlation relationship among data ...
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Hard in theory, easy in practice: Why graph isomorphism algorithms seem to be so effective
Graphs are everywhere. In discrete mathematics, they are structures that show the connections between points, much like a public transportation network. Mathematicians have long sought to develop ...
ABSTRACT: To effectively evaluate a system that performs operations on UML class diagrams, it is essential to cover a large variety of different types of diagrams. The coverage of the diagram space ...
ABSTRACT: To effectively evaluate a system that performs operations on UML class diagrams, it is essential to cover a large variety of different types of diagrams. The coverage of the diagram space ...
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