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A complete expressiveness hierarchy for subgraph gnns via subgraph weisfeiler-lehman tests
Recently, subgraph GNNs have emerged as an important direction for develo**
expressive graph neural networks (GNNs). While numerous architectures have been …
expressive graph neural networks (GNNs). While numerous architectures have been …
Weisfeiler and leman go machine learning: The story so far
In recent years, algorithms and neural architectures based on the Weisfeiler-Leman
algorithm, a well-known heuristic for the graph isomorphism problem, have emerged as a …
algorithm, a well-known heuristic for the graph isomorphism problem, have emerged as a …
A survey of graph neural networks and their industrial applications
H Lu, L Wang, X Ma, J Cheng, M Zhou - Neurocomputing, 2024 - Elsevier
Abstract Graph Neural Networks (GNNs) have emerged as a powerful tool for analyzing and
modeling graph-structured data. In recent years, GNNs have gained significant attention in …
modeling graph-structured data. In recent years, GNNs have gained significant attention in …
Fine-grained expressivity of graph neural networks
J Böker, R Levie, N Huang, S Villar… - Advances in Neural …, 2023 - proceedings.neurips.cc
Numerous recent works have analyzed the expressive power of message-passing graph
neural networks (MPNNs), primarily utilizing combinatorial techniques such as the $1 …
neural networks (MPNNs), primarily utilizing combinatorial techniques such as the $1 …
A review of graph-powered data quality applications for IoT monitoring sensor networks
The development of Internet of Things (IoT) technologies has led to the widespread adoption
of monitoring networks for a wide variety of applications, such as smart cities, environmental …
of monitoring networks for a wide variety of applications, such as smart cities, environmental …