Implementation of TimeNet autoencoder for embedding time series. Based on Malhotra et al. (2017) "TimeNet: Pre-trained deep recurrent neural network for time series classification", https://arxiv.org/abs/1706.08838
Addtitionally, this implementation supports features not given in the original paper:
- Support for variable length time series
- Time series normalization
- Variable-size batching with respect to non-uniform lengths of input time series
Implemented using TensorFlow 2.3.0 with Keras API. Experiments performed using time series data from http://www.cs.ucr.edu/~eamonn/time_series_data/.
Can be run from command line using main.py script. Sample data is provided in data folder
© Paulius Danenas (danpaulius(eta)gmail.com), 2020