SeismoGPT is a transformer autoregressive model achieving median normalized cross-correlation above 0.93 when forecasting synthetic three-component seismograms up to 240 s ahead from P- and S-wave context.
Applications of physics-informed neural networks in geosciences: From basic seismology to comprehensive environmental monitoring.Journal of Applied Geophysics, 2024
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Data-Driven Forecasting of three-Component Seismograms Using Transformer Architectures
SeismoGPT is a transformer autoregressive model achieving median normalized cross-correlation above 0.93 when forecasting synthetic three-component seismograms up to 240 s ahead from P- and S-wave context.