I have time-series as my data (one time-series per training example). I would like to encode the data within these series in a fixed-length vector of features using a keras model.
The problem is that my different examples' time-series don't have the same lengths. I haven't found a way of doing that. The problem of the encoder-decoder thing is that if the input lengths vary, the output lengths do this also. But I would like to have an output of length 10 let's say that would encode the data of the time-series, regardless of its length.
My question could have a strong link with: https://deepai.org/publication/towards-a-universal-neural-network-encoder-for-time-series but I haven't found any practical implementation.
Any help is very appreciated.