50 citations · 51 across the 2 of their papers we have counts for
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astro-ph.IM2020
Density Based Outlier Scoring on Kepler Data
Daniel Giles, Lucianne Walkowicz
In the present era of large scale surveys, big data presents new challenges to the discovery process for anomalous data. Such data can be indicative of systematic errors, extreme (…
astro-ph.IM2018★ 50 cited
Systematic Serendipity: A Test of Unsupervised Machine Learning as a Method for Anomaly Detection
Daniel Giles, Lucianne Walkowicz
Advances in astronomy are often driven by serendipitous discoveries. As survey astronomy continues to grow, the size and complexity of astronomical databases will increase, and the…