Results 21 to 30 of about 1,903,201 (339)
A graph neural network-enhanced knowledge graph framework for intelligent analysis of policing cases
Mathematical Biosciences and Engineering, 2023 In this paper, we model a knowledge graph based on graph neural networks, conduct an in-depth study on building knowledge graph embeddings for policing cases, and design a graph neural network-enhanced knowledge graph framework.
Hongqiang Zhu
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Spatio-temporal Graph Convolutional Neural Network: A Deep Learning Framework for Traffic Forecasting [PDF]
International Joint Conference on Artificial Intelligence, 2017 Timely accurate traffic forecast is crucial for urban traffic control and guidance. Due to the high nonlinearity and complexity of traffic flow, traditional methods cannot satisfy the requirements of mid-and-long term prediction tasks and often neglect ...
Ting Yu, Haoteng Yin, Zhanxing Zhu
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Point-GNN: Graph Neural Network for 3D Object Detection in a Point Cloud [PDF]
Computer Vision and Pattern Recognition, 2020 In this paper, we propose a graph neural network to detect objects from a LiDAR point cloud. Towards this end, we encode the point cloud efficiently in a fixed radius near-neighbors graph. We design a graph neural network, named Point-GNN, to predict the
Weijing Shi, R. Rajkumar
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RG-GCN: Improved Graph Convolution Neural Network Algorithm Based on Rough Graph
IEEE Access, 2022 The graph convolution neural network uses topological graph to portray inter-node relationships and update node features. However, the traditional topological graph can only describe the certain relationship between nodes (that is, the weight of the ...
Weiping Ding +7 more
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Survey of Knowledge Graph Reasoning Based on Representation Learning [PDF]
Jisuanji kexue, 2023 Knowledge graphs describe objective knowledge in the real world in a structured form,and are confronted with issues of completeness and newly-added knowledge.As an important means of complementing and updating knowledge graphs,know-ledge graph reasoning ...
LI Zhifei, ZHAO Yue, ZHANG Yan
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Simple and Efficient Heterogeneous Graph Neural Network [PDF]
AAAI Conference on Artificial Intelligence, 2022 Heterogeneous graph neural networks (HGNNs) have the powerful capability to embed rich structural and semantic information of a heterogeneous graph into node representations.
Xiaocheng Yang +4 more
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Graph Neural Network Defense Combined with Contrastive Learning [PDF]
Jisuanji kexue yu tansuo, 2023 Although graph neural networks have achieved good performance in the field of graph representation learning, recent studies have shown that graph neural networks are more susceptible to adversarial attacks on graph structure, namely, by adding well ...
CHEN Na, HUANG Jincheng, LI Ping
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Graph Neural Networks in Network Neuroscience
IEEE Transactions on Pattern Analysis and Machine Intelligence, 2023 Noninvasive medical neuroimaging has yielded many discoveries about the brain connectivity. Several substantial techniques mapping morphological, structural and functional brain connectivities were developed to create a comprehensive road map of neuronal activities in the human brain -namely brain graph.
Alaa Bessadok +2 more
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A federated graph neural network framework for privacy-preserving personalization [PDF]
Nature Communications, 2021 Graph neural network (GNN) is effective in modeling high-order interactions and has been widely used in various personalized applications such as recommendation.
Chuhan Wu +4 more
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Power System Network Topology Identification Based on Knowledge Graph and Graph Neural Network
Frontiers in Energy Research, 2021 The automatic identification of the topology of power networks is important for the data-driven and situation-aware operation of power grids. Traditional methods of topology identification lack a data-tolerant mechanism, and the accuracy of their ...
Changgang Wang, Jun An, Jun An, Gang Mu
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