“近年、Graph Neural Network（GNN）は推薦・化学・知識グラフなど様々な分野で使われていますが、2020年に DeepMind が提案した MeshGraphNets（MGN） は、その中でも特に”

“The paper's key finding is the development of FSF and its successful application in graph classification, leading to improved performance compared to existing methods, especially when integrated with graph neural networks.”

“Achieved a classification accuracy of 96.25% on the HCPTask dataset.”

“HeteroHBA consistently achieves higher attack success than prior backdoor baselines with comparable or smaller impact on clean accuracy.”

“The paper proposes an auxiliary task learning (ATL) method for reconstructing missing PMU data.”

“DUALFloodGNN achieves substantial improvements in predicting multiple hydrologic variables while maintaining high computational efficiency.”

“The likelihood can be expressed in terms of small subgraphs.”

“The paper highlights the effectiveness of various GNN models in detecting fraud and addresses challenges like class imbalance and fraudulent camouflage.”

“The GNN-TF model outperforms state-of-the-art methods, delivering superior predictive accuracy for predicting future tobacco usage.”

“A simple dynamic Graph Neural Network (GNN) is representative enough to outperform LLMs in debugging tabular log.”

“GRExplainer extracts node sequences as a unified feature representation, making it independent of specific input formats and thus applicable to both snapshot-based and event-based TGNNs.”

“Transformer models, which excel at handling long-term dependencies, have become significant architectural components for time series forecasting.”

“SimVC-CAS significantly improves predictive accuracy while providing interpretable, multiperspective reasoning, for example, approximately 25% relative improvement with respect to average precision@10.”

“BLISS adapts to evolving node importance, leading to more informed node selection and improved performance.”

“The proposed method not only outperforms existing graph-based models but also significantly surpasses conventional HGNNs in tasks that prioritize topological structure representation.”

“The proposed approach consistently outperforms baseline methods across multiple evaluation metrics, significantly improving both the accuracy and depth of reasoning, particularly in complex multi-hop and comparative reasoning scenarios.”

“The surrogate achieves sub angstrom level accuracy within the training horizon and exhibits stable behavior during short- to mid-horizon temporal extrapolation.”

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“we propose a Novel Graph-Sequence Learning Model for Inductive Text Classification (TextGSL) to address the previously mentioned issues.”

“The research focuses on a 'Multi-fidelity Double-Delta Wing Dataset' and its application to GNN-based aerodynamic field surrogates.”

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“MAPI-GNN is designed for multimodal medical diagnosis.”

“The paper likely explores the application of GNNs to model the complex relationships within IoT networks and the use of adversarial defense techniques to improve the robustness of the malware detection system.”

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“The research focuses on the classification of synthetic graph generative models.”

“The paper focuses on an Adaptive Patient-Centric GNN with Context-Aware Attention and Mini-Graph Explainability.”

“The research focuses on a Distributed Hierarchical Spatio-Temporal Edge-Enhanced Graph Neural Network for City-Scale Dynamic Logistics Routing.”

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“AL-GNN focuses on privacy-preserving and replay-free continual graph learning.”

“The article is from ArXiv, indicating it is likely a pre-print of a research paper.”

“The study utilizes Online Semi-Decentralized ST-GNNs.”

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“The article is a review and benchmark study.”

“The article likely presents a novel approach to simulating interferometers using GNNs, potentially offering advantages in terms of computational cost or simulation accuracy.”

“The research focuses on the application of GNNs to numerical data related to cementitious materials.”

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“The article is a 'complete guide' to the topic.”

“Empirical Robustness Across Domains.”

“The research focuses on semi-supervised multi-view graph convolutional networks.”

“The article is based on a paper from ArXiv, suggesting novel research.”

“The article is sourced from ArXiv, indicating it likely presents research findings.”

“The paper likely explores how Flow Matching can be integrated with GNNs to improve the accuracy of power flow predictions and guarantee constraint satisfaction.”

“LGAN is an efficient high-order graph neural network via the Line Graph Aggregation.”

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“The study focuses on using lightweight LLMs and GNNs.”

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“BugSweeper utilizes Graph Neural Networks for function-level detection of vulnerabilities.”

“The study integrates news sentiment and time series data with Graph Neural Networks.”

“The article's core focus is enhancing the explainability of Graph Neural Networks (GNNs).”