Conveners
Time domain: II
- Filomena Bufano (Istituto Nazionale di Astrofisica (INAF))
Current surveys are detecting thousands of supernovae (SNe) but only a small percentage is able to be classified using spectroscopy. To harness their full power, many surveys are now classifying SNe using ML algorithms. However, these algorithms rely on training sets which are usually built from spectroscopically classified SNe. In this talk, I will present an Active Learning recommendation...
R. Falco, N. Parmiggiani, A. Bulgarelli, G. Panebianco, M. Lombardi, L. Castaldini, A. Di Piano, V. Fioretti, C. Pittori, M. Tavani
In Multi-Messanger astronomy the rapid and precise detection of transient events such as Gamma-Ray Bursts (GRBs) is fundamental to alert the scientific community of new transients and allow them to perform follow-up observations. For this reason, many space...
Machine learning is often viewed as a black box when it comes to understanding its output, be it a decision or a score. Automatic anomaly detection is no exception to this rule, and quite often the astronomer is left to independently analyze the data in order to understand why a given event is tagged as an anomaly. Worst, the expert may end up scrutinizing over and over the same kind of rare...
