Siamese network vs DTW

Siamese network vs DTW

Hi! I'm looking to build and/or find similarities between multivariate time series. Knowing that in my dataset I know some labels and that in the future I will have new labels.

I want to know what are the advantages, disadvantages and differences between creating similarities from a Siamese network (with Tensorflow Similarity) and using DTW (dynamic time warping).

Thanks in advance for your feedback!

advantages dataset deeplearning disadvantages future labels multivariate network series tensorflow time series