Published March 1, 2019
| public
Journal Article
Preface to the Focus Section on Machine Learning in Seismology
- Creators
- Bergen, Karianne J.
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Chen, Ting
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Li, Zefeng
Abstract
Machine learning (ML) is a collection of algorithms and statistical models that enable computers to extract relevant patterns and information from large data sets. Unlike physical modeling approaches, in which scientists develop theories based on physical laws to compare with real‐world observations, ML approaches learn directly from data without explicitly reasoning about the underlying physical mechanisms.
Additional Information
© 2019 Seismological Society of America. Published Online 13 February 2019. The authors would like to thank all the authors for their contributions to this focus section. The authors are grateful to reviewers for their constructive and timely feedback. The authors thank SRL Editor-in-Chief Zhigang Peng for inviting us to be guest editors of this focus section and SRL Managing Editor Mary George for managing the focus section.Additional details
- Eprint ID
- 92921
- Resolver ID
- CaltechAUTHORS:20190214-082738908
- Created
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2019-02-14Created from EPrint's datestamp field
- Updated
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2021-11-16Created from EPrint's last_modified field
- Caltech groups
- Seismological Laboratory