Gated residual recurrent graphneural networksfor traffic prediction. Resource Allocation (A GNN-Based Federated Learning Framework for Resource Allocation in Wireless IoT Networks) A GNN-Based Federated Learning Framework for Resource Allocation in Wireless IoT Networks 借助于图的建模,无线物联网系统由图来...
在过去的几年里,图神经网络(Graph Neural Networks, GNN)已经成为人工智能领域的一个热门话题,它代表了一种在图数据上进行学习和推理的强大工具。随着数据量的爆炸式增长,尤其是结构化数据,在图形表示中捕获实体间复杂关系的需求日益增加。GNN的出现,为解决这一挑战提供了新的视角和方法。 本系列文章从GNN的基础概念...
between nodes and producinghigh-level representations of the graph input, graph neural networks (GNNs)have exploded onto various ML and AI fields, to learn from graph-structured data.Our review covers the latest progresses in GNN for the fundamental atomic task ofdata acquisition in AIoT. Instead...
A Survey on Graph Neural Networks in Intelligent Transportation Systems[J]. arXiv preprint arXiv:2401.00713, 2024. Link 2023 Journal Qi X, Yao J, Wang P, et al. Combining weather factors to predict traffic flow: A spatial‐temporal fusion graph convolutional network‐based deep learning ...
Road speed prediction, which is a sub-task of traffic flow forecasting, is challenging due to the complicated spatial dependencies characterizing road networks and dynamic temporal traffic patterns. Given the power of recurrent neural networks (RNNs) in learning temporal relations and graph neural ...
such as neural networks [15], Convolutional Neural Networks (CNN) and Recurrent Neural Networks (RNN) [16], Graph-Based Methods [17]. For example, aiming to solve the problem of detecting potential anomalies in microservices, Hasnain et al. [15] used recurrent neural networks (RNN) based ap...
AllegroGraph provides organizations with essential Knowledge Graph solutions, including Large Language Models (LLMs), Graph Neural Networks, Graph Virtualization, GraphQL, Apache Spark graph analytics, and Kafka streaming graph pipelines. These capabilities exemplify AllegroGraph’s leadership in empowering ...
A study to find a suitable temporal-based embedding model in detecting IoT malware through network analysis knowledge-graphnetwork-analysisembedding-modelsiot-securitytemporal-knowledge-graph UpdatedMay 18, 2021 Improve this page Add a description, image, and links to thetemporal-knowledge-graphtopic pag...
The 'Graph Partition Problem' refers to dividing a graph into two equal-size sets of vertices in a way that minimizes the number of edges going from one set to the other. It is a relevant problem in computer science, especially in parallel processing applications. AI generated definition based...
🙋 Please let us know if you find out a mistake or have any suggestions! 🌟 If you find this resource helpful, please consider to star this repository and cite our survey paper: @article{jin2024gnn4ts, title={A Survey on Graph Neural Networks for Time Series: Forecasting, Classification...