Machine learning applications for transient discovery facing Rubin Science
The Vera C. Rubin Observatory’s Legacy Survey of Space and Time (LSST) will revolutionise time-domain astronomy by producing millions of photometric alerts per night, requiring scalable and robust machine-learning (ML) methods for both variability characterisation and rapid transient identification. This thesis develop...