Picture for Emily J. Forsberg

Emily J. Forsberg

Integrating Machine Learning for Planetary Science: Perspectives for the Next Decade

Add code
Jul 29, 2020
Abigail R. Azari, John B. Biersteker, Ryan M. Dewey, Gary Doran, Emily J. Forsberg, Camilla D. K. Harris, Hannah R. Kerner, Katherine A. Skinner, Andy W. Smith, Rashied Amini(+6 more)
Figure 1 for Integrating Machine Learning for Planetary Science: Perspectives for the Next Decade
Figure 2 for Integrating Machine Learning for Planetary Science: Perspectives for the Next Decade
Figure 3 for Integrating Machine Learning for Planetary Science: Perspectives for the Next Decade

Machine learning (ML) methods can expand our ability to construct, and draw insight from large datasets. Despite the increasing volume of planetary observations, our field has seen few applications of ML in comparison to other sciences. To support these methods, we propose ten recommendations for bolstering a data-rich future in planetary science.

* 10 pages (expanded citations compared to 8 page submitted version for decadal survey), 3 figures, white paper submitted to the Planetary Science and Astrobiology Decadal Survey 2023-2032 
Viaarxiv icon
Github IconAccess Paper or Ask Questions
Twitter IconFacebook IconLinkedin IconWhatsapp IconMessenger Icon