The DOI matches its Crossref record; 16 of the 16 references it cites were found in a registry or an index.
Machine learning for data-driven discovery in solid Earth geoscience
Abstract
Automating geoscience analysis: Solid Earth geoscience is a field that has very large set of observations, which are ideal for analysis with machine-learning methods. Bergen et al.review how these methods can be applied to solid Earth datasets. Adopting machine-learning techniques is important for extracting information and for understanding the increasing amount of complex data collected in the geosciences. Science, this issue p.eaau0323
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Enhancing Debris Flow Warning via Machine Learning Feature Reduction and Model Selection
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Metadata
- Authors
- Bergen, K. J., Johnson, P. A., de Hoop, M. V., & Beroza, G. C.
- Venue
- Science
- Published
- 2019-03-22
- Volume
- 363
- Issue
- 6433
- ISSN
- 0036-8075 (ISSN-L)
- 1095-9203
- OpenAlex
- W2923222994
- Cited by
- 1,249
- References
- 16
- FWCI
- 40.90
- Type
- journal article
- Language
- en
- Open access
- closed
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