# Autoencoding time series for visualisation

@article{Gianniotis2015AutoencodingTS, title={Autoencoding time series for visualisation}, author={Nikolaos Gianniotis and Sven Dennis K{\"u}gler and Peter Tiňo and Kai Lars Polsterer and Ranjeev Misra}, journal={ArXiv}, year={2015}, volume={abs/1505.00936} }

We present an algorithm for the visualisation of time series. To that end we employ echo state networks to convert time series into a suitable vector representation which is capable of capturing the latent dynamics of the time series. Subsequently, the obtained vector representations are put through an autoencoder and the visualisation is constructed using the activations of the bottleneck. The crux of the work lies with defining an objective function that quantifies the reconstruction error of…

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