Machine learning for data-driven discovery in solid Earth geoscience

Karianne J. Bergen; Paul A. Johnson; Maarten V. de Hoop; Gregory C. Beroza

doi:10.1126/science.aau0323

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

Keywords

Solid earthEarth (classical element)AstrobiologyEarth scienceData scienceComputer scienceGeologyGeophysicsBiologyAstronomyPhysics

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Publication Info

Year: 2019
Type: review
Volume: 363
Issue: 6433
Citations: 1086
Access: Closed

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APA Style

                            
                                
                                    Karianne J. Bergen, 
                                
                                    Paul A. Johnson, 
                                
                                    Maarten V. de Hoop
                                
                                et al.
                            
                            (2019). 
                            Machine learning for data-driven discovery in solid Earth geoscience. 
                            Science
                            , 363
                            (6433)
                            .
                            https://doi.org/10.1126/science.aau0323
                        

Identifiers

DOI: 10.1126/science.aau0323