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Craters, Planets and Redshifts: Three applications of Machine Learning in Astrophysics

Kristen Menou (University of Toronto) // February 8, 2018


Abstract: I will describe, rather informally, three recent applications of machine learning in astrophysics: predicting the dynamical stability of planetary systems (Tamayo et al. 2016), cataloguing lunar craters (Silburt, Ali-Dib et al. 2018) and estimating photometric redshifts (Menou 2018). I will provide a brief introduction to supervised machine learning and deep learning, as needed to describe these results.

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