# A Survey on Graph Neural Networks for Time Series: Forecasting, Classification, Imputation, and Anom

**Link:**[https://arxiv.org/pdf/2307.03759.pdf](https://arxiv.org/pdf/2307.03759.pdf)

## Abstract

Key con of DL like RNN, CNN, Transformer: do not explicitly model the spatial relations existing between time series in non-Euclidean space.

GNN can overcome this. ![Alt text](https://169318583-files.gitbook.io/~/files/v0/b/gitbook-x-prod.appspot.com/o/spaces%2FUAYVuGJIcqGBOPcOsA14%2Fuploads%2Fgit-blob-89a63844c293c8444a40aa058bf2425094252f1b%2FGNNtable4ts.png?alt=media)
