DERVISI, Foteini, SEGOU, Margarita, POLI, Piero, BAPTIE, Brian, MAIN, Ian und CURTIS, Andrew, 2025. Towards a deep learning approach for short-term data-driven spatiotemporal seismicity rate forecasting. Earth, Planets & Space. 25 November 2025. Vol. 77, no. 1, p. 1-35. DOI 10.1186/s40623-025-02241-6.
Elsevier - Harvard (with titles)Dervisi, F., Segou, M., Poli, P., Baptie, B., Main, I., Curtis, A., 2025. Towards a deep learning approach for short-term data-driven spatiotemporal seismicity rate forecasting. Earth, Planets & Space 77, 1-35. https://doi.org/10.1186/s40623-025-02241-6
American Psychological Association 7th editionDervisi, F., Segou, M., Poli, P., Baptie, B., Main, I., & Curtis, A. (2025). Towards a deep learning approach for short-term data-driven spatiotemporal seismicity rate forecasting. Earth, Planets & Space, 77(1), 1-35. https://doi.org/10.1186/s40623-025-02241-6
Springer - Basic (author-date)Dervisi F, Segou M, Poli P, Baptie B, Main I, Curtis A (2025) Towards a deep learning approach for short-term data-driven spatiotemporal seismicity rate forecasting.. Earth, Planets & Space 77:1-35. https://doi.org/10.1186/s40623-025-02241-6
Juristische Zitierweise (Stüber) (Deutsch)Dervisi, Foteini/ Segou, Margarita/ Poli, Piero/ Baptie, Brian/ Main, Ian/ Curtis, Andrew, Towards a deep learning approach for short-term data-driven spatiotemporal seismicity rate forecasting., Earth, Planets & Space 2025, 1-35.