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New paper on predicting off-fault deformation from fault geometry

January 29, 2022 – 2:54 pm

Chaipornkaew, Laainam, Hanna M. Elston, Michele L. Cooke, Tapan Mukerji and Stephan Graham, accepted. Using Convolution Neural Networks to estimate off-fault deformation from fault maps,  Geophysical Research Letters. doi.org/10.1029/2021GL096854. 
(Open access preprint at doi:10.1002/essoar.10507909.1.)

plot on left shows the CNN prediction against the label truth. The graph at right shows the application of the experiment trained CNN on crustal fault maps.
Left: Correlation of prediction with true label from the strike-slip experiments.
Right: comparison of CNN predictions of off-fault deformation with three different types of geologic estimates.
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