EarthquakeNPP: Benchmark Datasets for Earthquake Forecasting with Neural Point Processes

Sam Stockman, Daniel Lawson, & Maximilian J. Werner

Published September 8, 2024, SCEC Contribution #14060, 2024 SCEC Annual Meeting Poster #212

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 for decades. Recent advances have led to Neural Point Processes (NPPs), which promise greater flexibility and improvements over classical models. However, the currently-used benchmark dataset for NPPs does not represent an up-to-date challenge in the seismological community since it lacks a key earthquake sequence from the region and improperly splits training and testing data. Furthermore, initial earthquake forecast benchmarking lacks a comparison to state-of-the-art earthquake forecasting models typically used by the seismological community. To address these gaps, we introduce EarthquakeNPP: a collection of benchmark datasets to facilitate testing of NPPs on earthquake data, accompanied by a credible implementation of the ETAS model. The datasets cover a range of small to large target regions within California, dating from 1971 to 2021, and include different methodologies for dataset generation. Using EarthquakeNPP, we benchmark three spatio-temporal NPPs against ETAS and find that, across all datasets, the ETAS model outperforms the NPPs in both spatial and temporal log-likelihood. These results indicate that current NPP implementations are not yet suitable for practical earthquake forecasting. However, EarthquakeNPP will serve as a platform for collaboration between the seismology and machine learning communities with the goal of improving earthquake predictability.

Citation
Stockman, S., Lawson, D., & Werner, M. J. (2024, 09). EarthquakeNPP: Benchmark Datasets for Earthquake Forecasting with Neural Point Processes. Poster Presentation at 2024 SCEC Annual Meeting.

Related Projects & Working Groups
Earthquake Forecasting and Predictability (EFP)