Deep-Learning the Time Domain. Issue Volume 14:Issue S339(2018) (November 2017) - Mahabal, A.; Sheth, K.; Gieseke, F.; Drake, A.; Djorgovski, G.; Graham, M. J.
Abstract: "Deep learning" is finding more and more applications everywhere, and astronomy is not an exception. This talk described the application of convolutional neural networks to time-domain astronomy, specifically to light-curves of sources. The work that is discussed is based on a published paper to which reference can be made for more detail. The talk finished with a note cautioning new practitioners about the pitfalls lurking in out-of-the-box use of deep-learning techniques.