A Survey on Graph Neural Networks for Time Series: Forecasting, Classification, Imputation, and Anomaly Detection. (arXiv:2307.03759v2 [cs.LG] UPDATED)

Time series are the primary data type used to record dynamic system
measurements and generated in great volume by both physical sensors and online
processes (virtual sensors). Time series analytics is therefore crucial to
unlocking the wealth of information implicit in available data. With the recent
advancements in graph neural networks (GNNs), there has been a surge in
GNN-based approaches for time series analysis. These approaches can explicitly
model inter-temporal and inter-variable relationships, which traditional and
other deep neural network-based …

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