Towards a Deeper Understanding of Sleep Stages through their Representation in the Latent Space of Variational Autoencoders.
Luka BiedebachMatias RusanenTimo LeppänenAnna Sigridur IslindBenedikt ThordarsonErna Sif ArnardóttirMaria ÓskarsdóttirHenri KorkalainenSami NikkonenSamu KainulainenJuha TöyräsSami MyllymaaPublished in: HICSS (2023)
Keyphrases
- deeper understanding
- latent space
- latent variables
- low dimensional
- gaussian process
- generative model
- lower dimensional
- feature space
- manifold learning
- dimensionality reduction
- matrix factorization
- probabilistic latent semantic analysis
- high dimensional
- denoising
- parameter space
- distance metric
- image representation
- transfer learning
- topic models
- image segmentation
- collaborative filtering
- data points
- probabilistic model
- keywords
- training data