Machine Learning in Astronomy (IAU S368)
Possibilities and Pitfalls
Herausgeber: Mahabal, Ashish; McIver, Jess; Fluke, Christopher
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Erscheint vorauss. 30. September 2025
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IAU S368 addresses graduate students and professional astronomers who wish to leverage machine learning to unlock the potential of modern data-rich surveys and deep images, as well as archival data. Researchers at the frontiers share best practices in applied machine learning that are relevant to astronomy and other data-rich fields.
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