CaltechAUTHORS
  A Caltech Library Service

Preface to the Focus Section on Machine Learning in Seismology

Bergen, Karianne J. and Chen, Ting and Li, Zefeng (2019) Preface to the Focus Section on Machine Learning in Seismology. Seismological Research Letters, 90 (2A). pp. 477-480. ISSN 0895-0695. doi:10.1785/0220190018. https://resolver.caltech.edu/CaltechAUTHORS:20190214-082738908

Full text is not posted in this repository. Consult Related URLs below.

Use this Persistent URL to link to this item: https://resolver.caltech.edu/CaltechAUTHORS:20190214-082738908

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.


Item Type:Article
Related URLs:
URLURL TypeDescription
https://doi.org/10.1785/0220190018DOIArticle
ORCID:
AuthorORCID
Chen, Ting0000-0002-9599-871X
Li, Zefeng0000-0003-4405-8872
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.
Group:Seismological Laboratory
Issue or Number:2A
DOI:10.1785/0220190018
Record Number:CaltechAUTHORS:20190214-082738908
Persistent URL:https://resolver.caltech.edu/CaltechAUTHORS:20190214-082738908
Official Citation:Karianne J. Bergen, Ting Chen, Zefeng Li; Preface to the Focus Section on Machine Learning in Seismology. Seismological Research Letters ; 90 (2A): 477–480. doi: https://doi.org/10.1785/0220190018
Usage Policy:No commercial reproduction, distribution, display or performance rights in this work are provided.
ID Code:92921
Collection:CaltechAUTHORS
Deposited By: Tony Diaz
Deposited On:14 Feb 2019 17:26
Last Modified:16 Nov 2021 16:54

Repository Staff Only: item control page