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Title: Machine learning for data-driven discovery in solid Earth geoscience
Understanding the behavior of Earth through the diverse fields of the solid Earth geosciences is an increasingly important task. It is made challenging by the complex, interacting, and multiscale processes needed to understand Earth’s behavior and by the inaccessibility of nearly all of Earth’s subsurface to direct observation. Substantial increases in data availability and in the increasingly realistic character of computer simulations hold promise for accelerating progress, but developing a deeper understanding based on these capabilities is itself challenging. Machine learning will play a key role in this effort. We review the state of the field and make recommendations for how progress might be broadened and accelerated.  more » « less
Award ID(s):
1818579
PAR ID:
10107939
Author(s) / Creator(s):
; ; ;
Date Published:
Journal Name:
Science
Volume:
363
Issue:
6433
ISSN:
0036-8075
Page Range / eLocation ID:
eaau0323
Format(s):
Medium: X
Sponsoring Org:
National Science Foundation
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