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cs.LG2024
Back to Bayesics: Uncovering Human Mobility Distributions and Anomalies with an Integrated Statistical and Neural Framework
Minxuan Duan, Yinlong Qian, Lingyi Zhao +4
Existing methods for anomaly detection often fall short due to their inability to handle the complexity, heterogeneity, and high dimensionality inherent in real-world mobility data…
cs.LG2024
NUMOSIM: A Synthetic Mobility Dataset with Anomaly Detection Benchmarks
Chris Stanford, Suman Adari, Xishun Liao +10
Collecting real-world mobility data is challenging. It is often fraught with privacy concerns, logistical difficulties, and inherent biases. Moreover, accurately annotating anomali…