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About this paper
Hendrik Mehrtens, Florian Buettner, Oliver Stegle
The authors compare flexible Hawkes processes with neural models for autoregressive next-event prediction, where each event has a time and type. They add spline-based intensity shapes and evaluate both families in a shared framework across seven datasets. Flexible Hawkes models largely close the benchmark gap, while added flexibility mainly improves timing; neural models retain advantages on Amazon and MIMIC-IV.
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