Results 81 to 90 of about 6,341,676 (193)
Spatio-Temporal Joint Graph Convolutional Networks for Traffic Forecasting [PDF]
, 2023 Recent studies have shifted their focus towards formulating traffic forecasting as a spatio-temporal graph modeling problem. Typically, they constructed a static spatial graph at each time step and then connected each node with itself between adjacent ...
Philip S. Yu +15 more
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Enhancing Image Classification using Graph Attention Networks
Iraqi Journal for Computers and InformaticsExcellent performance in artificial intelligence image classification leads to extensive applications throughout areas such as healthcare facilities, robotic systems and multimedia platforms.
Hasan Maher Ahmed
doaj +1 more source
Graph Attention Networks in Exchange Rate Forecasting
EconometricsExchange rate forecasting is an important issue in financial market analysis. Currency rates form a dynamic network of connections that can be efficiently modeled using graph neural networks (GNNs).
Joanna Landmesser-Rusek +1 more
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Graph Attention Topic Modeling Network
Proceedings of The Web Conference 2020, 2020 Existing topic modeling approaches possess several issues, including the overfitting issue of Probablistic Latent Semantic Indexing (pLSI), the failure of capturing the rich topical correlations among topics in Latent Dirichlet Allocation (LDA), and high inference complexity.
Liang Yang 0002 +6 more
openaire +2 more sources
Android malware detection based on graph attention networks
四川大学学报. 自然科学版, 2022 The explosive growth of Android malware has put forward more efficient and accurate requirements for malware detection methods. In the early years, detection methods were mainly based on features such as permissions and opcode sequences.
YUE Zi-Wei, FANG Yong, ZHANG Lei
doaj
Adaptive Structural Similarity Guided GCN–GAT Framework for Robust Link Prediction [PDF]
International Journal of Mathematical, Engineering and Management SciencesSocial Network Analysis (SNA) has experienced major advancements with the growth of technology, which has made link prediction an important aspect of SNA, particularly regarding social network applications, recommendation systems, and various biological ...
Shambhu Kumar +2 more
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Evaluating the role of attention-based message passing in explainable molecular toxicity prediction
In Silico Research in BiomedicineThe use of Graph Neural Networks (GNNs) has recently been shown to effectively encode molecular toxicity prediction problems where a desirable learning procedure from graph-based representations of molecules can occur without the need for any hand ...
Gurojaspreet Kaur
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Review of Graph Neural Networks [PDF]
Jisuanji kexueWith the rapid development of artificial intelligence,deep learning has achieved great success in data that can be represented in Euclidean spaces,such as images,text,and speech.However,it has been difficult to apply deep learning to non-Eucli-dean ...
HOU Lei, LIU Jinhuan, YU Xu, DU Junwei
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Multi-attention graph neural networks for city-wide bus travel time estimation using limited data
, 2022 Multi-attention graph neural networks for city-wide bus travel time estimation using limited ...
Sutharshan Rajasegarar (13095816) +3 more
core +1 more source
User Identity Linkage Across Social Networks by Heterogeneous Graph Attention Network Modeling
Applied Sciences, 2020 Today, social networks are becoming increasingly popular and indispensable, where users usually have multiple accounts. It is of considerable significance to conduct user identity linkage across social networks.
Ruiheng Wang +5 more
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