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The traffic4cast model #25

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@Scienceseb

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@Scienceseb

In your article you wrote in the traffic4cast section:

To cope with high-dimensional input frames, we apply the autoencoder architecture of U-Net [88] to the network backbone of PredRNN. Specifically, the decoder of U-Net contains four ST- LSTM layers, and the CNN encoder takes both traffic flow maps and spatiotemporal memory states as inputs.

The code for this model is not available on this GitHub repo, can you make it available please.

Thanks a lot!

Kind regards,
Sébastien de Blois

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