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Interpretable Machine Learning for Astrophysics, using Symbolic Regression and Graph Neural Networks

Speaker
Miles Cranmer (Princeton University)
Event date
Venue
online (only)
Event type

In this talk I will argue two points. 1) Symbolic regression, a machine learning technique that fits data by iteratively searching the space of all possible analytic equations, should be a standard machine learning algorithm in astrophysics. 2) Symbolic regression can be extended to high-dimensional spaces, such as to models for N-body simulations, using the method we have developed.

APS Outstanding Referee

C. Herdeiro was nominated a 2021 Outstanding Referee by the American Physical Society (APS). The Outstanding Referee program was instituted in 2008 to recognize scientists who have been exceptionally helpful in assessing manuscripts for publication in the APS journals. This highly selective program annually recognizes about 150 of the roughly 71,000 currently active referees.