About this document
CLARA: Unsupervised Transit Detection Framework by hoanglm22407c is a document available to read on EtoBox.
The document presents CLARA, a modular framework for unsupervised transit detection in TESS light curves using Unsupervised Random Forests (URFs) and morphological similarity analysis. The study investigates the impact of synthetic training set design on URF performance and the correlation of URF anomaly scores with genuine astrophysical phenomena. The results demonstrate a significant improvement in detection rates compared to baseline methods, with the framework designed for both machine learning and astr
- Author
- hoanglm22407c
- Language
- EN