inisamuel/thesis

Code for master's thesis

Symbolic Representation of Time Series Data using VAEs with Discrete Latent Variables

Summary

We aim to learn symbolic representations of time series data in an unsupervised manner using variational autoencoders (VAEs) with categorical latent variables + Gumbel-softmax reparametrization

MLFlow is used to log metrics, parameters and artefacts