Graph neural networks by Lian, Ran

“…In recent years, Graph Neural Networks (GNNs) have become increasingly attractive methods for molecular property prediction due to their abilities to analyze graph structural data with chemical structures being easily displayed as graphs. …”
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Survey on Graph Neural Networks by Georgios Gkarmpounis, Christos Vranis, Nicholas Vretos, Petros Daras

Subjects: “…Graph neural networks (GNNs)…”
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Schatten Graph Neural Networks by Youfa Liu, Yongyong Chen, Guo Chen, Jiawei Zhang

“…Recalling recent works on graph neural networks, we found that imposing graph smoothing via Frobenius norm was proven to be effective in the architecture of graph neural networks from the standpoint of the graph signal processing. …”
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Federated graph neural network by Koh, Tat You @ Arthur

“…Graph Neural Networks is a form of machine learning that has seen significant growth in popularity and use, owing to their natural affinity for capturing implicit representations that exist in real-world phenomena. …”
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Mathematical Expressiveness of Graph Neural Networks by Guillaume Lachaud, Patricia Conde-Cespedes, Maria Trocan

Subjects: “…graph neural networks…”
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Evaluating explainability for graph neural networks by Chirag Agarwal, Owen Queen, Himabindu Lakkaraju, Marinka Zitnik

“…Abstract As explanations are increasingly used to understand the behavior of graph neural networks (GNNs), evaluating the quality and reliability of GNN explanations is crucial. …”
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Graph neural network with knowledge graph by Ang, Qi Xuan

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Benchmarking novel graph neural networks by Bhagwat, Abhishek

“…We can make use of Graph Neural Networks (GNNs) to analyse physical systems which can be modelled as graphs. …”
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Federated learning for graph neural networks by Yan, Yige

“…This dissertation investigates the combination of graph neural networks (GNNs) and federated learning (FL) for addressing practical problems while preserving data privacy and reducing computational complexity. …”
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A study on graph neural networks by Choo, Patricia Yu Wei

“…This report investigates various Graph Neural Network (GNN) models and its performance and stability. …”
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Graph neural network for anomaly detection by Yeo, Ming Hong

“…Graph Neural Networks (GNNs) have gained prominence in the realm of anomaly detection on graph-structured data, a critical task in various fields such as cybersecurity, fraud detection, and network monitoring. …”
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Graph neural network in recommender systems by Koh, Yi Kun

“…The reason why Graph Neural Networks (GNNs) have become popular in these systems is because they are well-suited to handle the graph-like nature of the data and are superior in learning graph representations. …”
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Graph neural networks for questions and answers by Mah, Caleb

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Graph neural networks for network analysis by He, Y

“…<p>With an increasing number of applications where data can be represented as graphs, graph neural networks (GNNs) are a useful tool to apply deep learning to graph data. …”

Orbit-equivariant graph neural networks by Morris, M, Grau, BC, Horrocks, I

“…Equivariance is an important structural property that is captured by architectures such as graph neural networks (GNNs). However, equivariant graph functions cannot produce different outputs for similar nodes, which may be undesirable when the function is trying to optimize some global graph property. …”

GNNGLY: Graph Neural Networks for Glycan Classification by Alhasan Alkuhlani, Walaa Gad, Mohamed Roushdy, Abdel-Badeeh M. Salem

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Quantized Graph Neural Networks for Image Classification by Xinbiao Xu, Liyan Ma, Tieyong Zeng, Qinghua Huang

Subjects: “…graph neural network…”
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Hierarchical Model Selection for Graph Neural Networks by Yuga Oishi, Ken Kaneiwa

Subjects: “…Graph neural networks (GNNs)…”
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On the distribution alignment of propagation in graph neural networks by Qinkai Zheng, Xiao Xia, Kun Zhang, Evgeny Kharlamov, Yuxiao Dong

Subjects: “…Graph neural networks…”
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Global explanation supervision for Graph Neural Networks by Negar Etemadyrad, Yuyang Gao, Sai Manoj Pudukotai Dinakarrao, Liang Zhao

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