3 papers
astro-ph.IM2026
A targeted machine learning approach for detecting diffuse radio emission with Astronomaly: Protege
Verlon Etsebeth, Michelle Lochner, Konstantinos Kolokythas +2
Diffuse radio emission in galaxy clusters, such as radio halos, relics, and mini halos, is a key tracer of non-thermal processes, turbulence, and magnetic fields within the intra-c…
astro-ph.IM2025
Finding radio transients with anomaly detection and active learning based on volunteer classifications
Alex Andersson, Chris Lintott, Rob Fender +9
In this work we explore the applicability of unsupervised machine learning algorithms to finding radio transients. Facilities such as the Square Kilometre Array (SKA) will provide…
astro-ph.IM2024
A Classifier-Based Approach to Multi-Class Anomaly Detection for Astronomical Transients
Rithwik Gupta, Daniel Muthukrishna, Michelle Lochner
Automating real-time anomaly detection is essential for identifying rare transients, with modern survey telescopes generating tens of thousands of alerts per night, and future tele…