2022/06/04 by Shiying Li, Li, Shiying, Abu Hasnat Mohammad Rubaiyat +3
Medicine · Computer Science · Health Professions · #Advanced Neuroimaging Techniques and Applications #Anomaly Detection Techniques and Applications #Balance, Gait, and Falls Prevention
paper · pdf · doi:10.48550/arxiv.2206.01984
Transport-based metrics and related embeddings (transforms) have recently been used to model signal classes where nonlinear structures or variations are present. In this paper, we study the geodesic properties of time series data with a generalized Wasserstein metric and the geometry related to their signed cumulative distribution transforms in the embedding space. Moreover, we show how understanding such geometric characteristics can provide added interpretability to certain time series classifiers, and be an inspiration for more robust classifiers.