Machine Learning for Transient Classification

Abstract

We organized Workshop 13, Machine learning for transient classification, into two distinct question-and-answer parts. The first was a so-called ‘idiot session’, in which basic questions about machine learning and artificial intelligence were elicited from the audience. The second focussed discussions on the application of artificial intelligence to transient astronomy.

The workshop proved highly successful. The room was packed, and the many interesting questions and discussions were good preparation for the presentation to be made on ‘machine learning’ during the plenary session the following day.

The workshop clearly reflected the general awareness and excitement in the community for the potential of machine learning in regard to transient detections in astronomy in the era of ZTF, LSST, LIGO and the SKA. Several of the presentations at this Symposium had already been exhibiting specific attention to the roles of machine-learning techniques and products. The extent to which the younger generations were being involved was clearly noticeable, and that augured well for research into workable solutions for astronomy’s ‘Big Data’ problems which – as stated frequently at this conference – are only just around the corner.