Forecasting the 2016-2017 Central Apennines Earthquake Sequence with a Neural Point Process

Abstract

We construct a new machine learning variant of point processes for short-term earthquake forecasting enhanced catalogs.• The neural point process gains higher forecasting performance from the low magnitude data than ETAS and is faster to train.• This forecasting performance on the 2016 Central Italy sequence motivates continued development in this class of models.