Feb. 2, 2024, 9:46 p.m. | Anita Graser Anahid Jalali Jasmin Lampert Axel Wei{\ss}enfeld Krzysztof Janowicz

cs.LG updates on arXiv.org arxiv.org

Trajectory data combines the complexities of time series, spatial data, and (sometimes irrational) movement behavior. As data availability and computing power have increased, so has the popularity of deep learning from trajectory data. This review paper provides the first comprehensive overview of deep learning approaches for trajectory data. We have identified eight specific mobility use cases which we analyze with regards to the deep learning models and the training data used. Besides a comprehensive quantitative review of the literature since …

availability behavior complexities computing computing power cs.lg data deep learning overview paper power review series spatial time series trajectory

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