dil8

Graph neural networks are deep learning models that trained on graph data.

I agree, combining GNNs with temporal signals and dynamics graphs make them so expressive. Another great recent paper on this topic https://arxiv.org/abs/2310.15978

Check out dgl (https://github.com/dmlc/dgl). A lot of papers and algorithms are implemented in the examples section.

> If you want to predict (multiple) time series using multiple series as input/predictors, that's a whole new level of difficulty. I don't know of a good automatic/fast/scalable approach that properly guards against overfitting

Have you had a look at algorithms contained in pytorch forcasting? https://pytorch-forecasting.readthedocs.io/en/latest/

follow on article https://ftalphaville.ft.com/2018/04/19/1524132443000/Deutsch...