311 citations · 549 across the 4 of their papers we have counts for
7 papers
Unsupervised machine learning for transient discovery in Deeper, Wider, Faster light curves
Sara Webb, Michelle Lochner, Daniel Muthukrishna +7
Identification of anomalous light curves within time-domain surveys is often challenging. In addition, with the growing number of wide-field surveys and the volume of data produced…
Using machine learning for transient classification in searches for gravitational-wave counterparts
Cosmin Stachie, Michael W. Coughlin, Nelson Christensen +1
The large sky localization regions offered by the gravitational-wave interferometers require efficient follow-up of the many counterpart candidates identified by the wide field-of-…
RAPID: Early Classification of Explosive Transients using Deep Learning
Daniel Muthukrishna, Gautham Narayan, Kaisey S. Mandel +2
We present RAPID (Real-time Automated Photometric IDentification), a novel time-series classification tool capable of automatically identifying transients from within a day of the…
4MOST: Project overview and information for the First Call for Proposals
R. S. de Jong, O. Agertz, A. Agudo Berbel +335
We introduce the 4-metre Multi-Object Spectroscopic Telescope (4MOST), a new high-multiplex, wide-field spectroscopic survey facility under development for the four-metre-class Vis…
Models and Simulations for the Photometric LSST Astronomical Time Series Classification Challenge (PLAsTiCC)
R. Kessler, G. Narayan, A. Avelino +26
We describe the simulated data sample for the "Photometric LSST Astronomical Time Series Classification Challenge" (PLAsTiCC), a publicly available challenge to classify transient…
DASH: Deep Learning for the Automated Spectral Classification of Supernovae and their Hosts
Daniel Muthukrishna, David Parkinson, Brad Tucker
We present DASH (Deep Automated Supernova and Host classifier), a novel software package that automates the classification of the type, age, redshift, and host galaxy of supernova…