46 citations · 49 across the 2 of their papers we have counts for
2 papers
astro-ph.SR2020★ 3 cited
Data-driven derivation of stellar properties from photometric time series data using convolutional neural networks
Kirsten Blancato, Melissa Ness, Daniel Huber +2
Stellar variability is driven by a multitude of internal physical processes that depend on fundamental stellar properties. These properties are our bridge to reconciling stellar ob…
astro-ph.SR2020★ 46 cited
Exploring the evolution of stellar rotation using Galactic kinematics
Ruth Angus, Angus Beane, Adrian M. Price-Whelan +9
The rotational evolution of cool dwarfs is poorly constrained after around 1-2 Gyr due to a lack of precise ages and rotation periods for old main-sequence stars. In this work we u…