Laboratory earthquake forecasting: A machine learning competition [Earth, Atmospheric, and Planetary Sciences]
Earthquake prediction, the long-sought holy grail of earthquake science, continues to confound Earth scientists. Could we make advances by crowdsourcing, drawing from the vast knowledge and creativity of the machine learning (ML) community? We used Google’s ML competition platform, Kaggle, to engage the worldwide ML community with a competition to...
Source: Proceedings of the National Academy of Sciences - Category: Science Authors: Paul A. Johnson, Bertrand Rouet-Leduc, Laura J. Pyrak-Nolte, Gregory C. Beroza, Chris J. Marone, Claudia Hulbert, Addison Howard, Philipp Singer, Dmitry Gordeev, Dimosthenis Karaflos, Corey J. Levinson, Pascal Pfeiffer, Kin Ming Puk, Walter Reade Tags: Earth, Atmospheric, and Planetary Sciences, Perspectives Source Type: research
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