WebAbstract. Modeling multivariate time series (MTS) is critical in modern intelligent systems. The accurate forecast of MTS data is still challenging due to the complicated latent variable correlation. Recent works apply the Graph Neural Networks (GNNs) to the task, with the basic idea of representing the correlation as a static graph. WebJan 26, 2024 · Nowadays, graph neural networks are being applied to a variety of fields like NLP, time series forecasting, clustering, etc. When we apply a graph neural network to the time series data, we call it the Spatio-temporal graph neural network. In this article, we will discuss the Spatio-temporal graph neural network in detail with its applications.
TodyNet: Temporal Dynamic Graph Neural Network for …
WebApr 11, 2024 · Multivariate time series classification (MTSC) is an important data mining task, which can be effectively solved by popular deep learning technology. Unfortunately, … WebMar 19, 2024 · This is a PyTorch implementation of the paper: Connecting the Dots: Multivariate Time Series Forecasting with Graph Neural Networks, published in KDD … the bride shop on salt lake city utah in 2020
Graph Neural Network-Based Anomaly Detection in Multivariate Time Series
WebThe most suitable type of graph neural networks for multivari-ate time series is spatial-temporal graph neural networks. Spatial-temporal graph neural networks take multivariate time series and an external graph structure as inputs, and they aim to predict fu-ture values or labels of multivariate time series. Spatial-temporal WebIn this paper, we propose Spectral Temporal Graph Neural Network (StemGNN) to further improve the accuracy of multivariate time-series forecasting. StemGNN captures inter-series correlations and temporal dependencies jointly in the spectral domain . WebMar 19, 2024 · To enable accurate forecasting on correlated time series, we proposes graph attention recurrent neural networks.First, we build a graph among different entities by taking into account spatial proximity and employ a multi-head attention mechanism to derive adaptive weight matrices for the graph to capture the correlations among vertices … the bride sting