Deep autoencoders outperform PCA and VAE variants on a composite of reconstruction MSE and interpretability metrics when reducing runner wearable data to a single latent performance score.
High-intensity interval training, solu- tions to the programming puzzle: Part II: anaerobic energy, neuromus- cular load and practical applications,
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Autoencoder Architectures for Athlete Performance Scoring from Wearable Telemetry
Deep autoencoders outperform PCA and VAE variants on a composite of reconstruction MSE and interpretability metrics when reducing runner wearable data to a single latent performance score.