Machine learning in astronomy : possibilities and pitfalls : proceedings of the 368th Symposium of the International Astronomical Union, Busan, Republic of Korea, 2-4 August, 2022

Author(s)

• International Astronomical Union. Symposium
• McIver, Jess
• Mahabal, Ashish
• Fluke, Christopher

Bibliographic Information

Machine learning in astronomy : possibilities and pitfalls : proceedings of the 368th Symposium of the International Astronomical Union, Busan, Republic of Korea, 2-4 August, 2022

edited by Jess McIver, Ashish Mahabal, Christopher Fluke

（IAU symposium and colloquium proceedings series, . IAU symposium ; 368）（Proceedings of the International Astronomical Union）

Cambridge University Press, 2025

• : hardback

Note

Content Type: text (ncrcontent), Media Type: unmediated (ncrmedia), Carrier Type: volume (ncrcarrier)

At head of title: International Astronomical Union, Union Astronomique Internationale

Includes bibliographical references and index

Details

• NCID: BD13930510
• ISBN:
  • 9781009345194
• Country Code: uk
• Title Language Code: eng
• Text Language Code: eng
• Place of Publication: Cambridge
• Pages/Volumes: xiii, 137 pages
• Size: 26 cm
• Parent Bibliography ID:
  • BA71935870
  • BB23062110