Before installation, it’s crucial to understand that Microsoft Graph is a RESTful web API that integrates various Microsoft services. You only need to authenticate once to access data across these ...
Abstract: Graph neural networks (GNNs) have drawn much attention for predicting the remaining useful life (RUL) due to their excellent performance in processing correlation relationships among data.
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 ...
Abstract: Smart contracts suffer from critical vulnerabilities such as reentrancy attacks, delegate call misuse, and timestamp dependencies, posing significant risks when deployed in smart grids. This ...
A Python implementation of a graph isomorphism algorithm based on gossip fingerprinting. The algorithm computes structural fingerprints for graph vertices to determine isomorphism. The gossip ...
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 ...
Article subjects are automatically applied from the ACS Subject Taxonomy and describe the scientific concepts and themes of the article. In response to the aforementioned challenges mentioned above, ...
A fundamental challenge in advancing AI research lies in developing systems that can autonomously perform structured reasoning and dynamically expand domain knowledge. Traditional AI models often rely ...
Given a pair of directed line graphs, the problem of ascertaining whether or not they are isomorphic is one for which no efficient algorithmic solution is known. Since a straightforward enumerative ...
Graph Neural Networks (GNNs) have gained considerable attention in recent years. Despite the surge in innovative GNN architecture designs, research heavily relies on the same 5-10 benchmark datasets ...
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