text: Paper proposes to use a convolutional network with 3 layers (convolutional + maxpoolong + fully connected layers) to embed time series in a new space such that an Euclidian distance is effective to perform a classification.  The algorithm is simple and experiments show that it is effective on a limited benchmark.  It would be interesting to enlarge the dataset to be able to compare statistically the results with state-of-the-art algorithms.  In addition, Authors compare themselves with time series metric learning and generalization of DTW algorithms.  It would also be interesting to compare with other types of time series classification algorithms (Bagnall 2016) .