AI RESEARCH
EarthquakeNPP: A Benchmark for Earthquake Forecasting with Neural Point Processes
arXiv CS.LG
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ArXi:2410.08226v3 Announce Type: replace-cross For decades, classical point process models, such as the epidemic-type aftershock sequence (ETAS) model, have been widely used for forecasting the event times and locations of earthquakes. Recent advances have led to Neural Point Processes (NPPs), which promise greater flexibility and improvements over such classical models. However, the currently-used benchmark for NPPs does not represent an up-to-date challenge in the seismological community, since it contains data leakage and omits the largest earthquake sequence from the region.