H Ghaderi, B Foreman, A Nayebi, S Tipirneni… - Journal of biomedical …, 2023 - Elsevier
Self-supervised learning approaches provide a promising direction for clustering
multivariate time-series data. However, real-world time-series data often include missing …

[HTML][HTML] A pipeline architecture for feature-based unsupervised clustering using multivariate time series from HPC jobs

J Enes, RR Expósito, J Fuentes, JL Cacheiro… - Information Fusion, 2023 - Elsevier
Time series are key across industrial and research areas for their ability to model behaviour
across time, making them ideal for a wide range of use cases such as event monitoring …

[HTML][HTML] Mining Spatiotemporal Mobility Patterns Using Improved Deep Time Series Clustering

Z Zhang, D Li, Z Zhang, N Duffield - ISPRS International Journal of Geo …, 2024 - mdpi.com
Mining spatiotemporal mobility patterns is crucial for optimizing urban planning, enhancing
transportation systems, and improving public safety by providing useful insights into human …