Time-series dataset similarity is defined via the Wasserstein distance between fitted multivariate normal distributions, and the distance shows partial correlation with foundation model inference loss.
Research on healthy anomaly detection model based on deep learning from multiple time-series physiological signals.Scientific Programming, 2016(1):5642856,
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Measuring Time-Series Dataset Similarity using Wasserstein Distance
Time-series dataset similarity is defined via the Wasserstein distance between fitted multivariate normal distributions, and the distance shows partial correlation with foundation model inference loss.