http://arxiv.org/abs/2211.16782
Machine Learning is a powerful tool for astrophysicists, which has already had significant uptake in the community. But there remain some barriers to entry, relating to proper understanding, the difficulty of interpretability, and the lack of cohesive training. In this discussion session we addressed some of these questions, and suggest how the field may move forward.
G. Cabrera, S. Hong, L. Nakazono, et. al.
Thu, 1 Dec 22
46/85
Comments: 6 pages. Prepared for the proceedings of the International Astronomical Union Symposium 368 “Machine Learning in Astronomy: Possibilities and Pitfalls”
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