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Found 4 papers, 3 papers with code
Exoplanet Detection using Machine Learning
For the Transiting Exoplanet Survey Satellite (TESS) data, we found our method can classify light curves with an accuracy of 0. 98, and is able to identify planets with a recall of 0. 82 at a precision of 0. 63.
GalaxyNet: Connecting galaxies and dark matter haloes with deep neural networks and reinforcement learning in large volumes
GalaxyNet is then trained with a reinforcement learning approach: for a fixed set of weights and biases, we compute the galaxy properties for all haloes and then derive mock statistics (stellar mass functions, cosmic and specific SFRs, quenched fractions, and clustering).
Astrophysics of Galaxies Data Analysis, Statistics and Probability
EMERGE - An empirical model for the formation of galaxies since $z\sim10$
Galaxies that are quenched at $z=0$ typically have a higher peak star formation rate compared to their star-forming counterparts.
Astrophysics of Galaxies
A Cosmic Variance Cookbook
This implies that cosmic variance is a significant source of uncertainty at z=2 for small fields and massive galaxies, while for larger fields and intermediate mass galaxies cosmic variance is less serious.
Cosmology and Nongalactic Astrophysics
