Closed timpitman closed 4 years ago
One approach here might be generalising the transposition for graph convolution to include some reshaping. For this, the input would have shape something like (batch dim, num nodes, time steps, variate dimension)
, and the be reshaped to run graph convolution on time steps * variate dimension
values, and LSTM on num nodes * variate dimension
values:
Description
Can we use Keras's existing multi-variate LSTM?
User Story
As a ...
I want to [accomplish some things]
So that [achieve a larger goal]
Done Checklist