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20152026
most citedPhotometric Supernova Classification With Machine Learning

197 citations · 1.3k across the 38 of their papers we have counts for

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Showing 2018Show all

8 papers · 1 filter

astro-ph.IM2018★ 13 cited

Optimizing the LSST Observing Strategy for Dark Energy Science: DESC Recommendations for the Wide-Fast-Deep Survey

Michelle Lochner, Daniel M. Scolnic, Humna Awan +33

Cosmology is one of the four science pillars of LSST, which promises to be transformative for our understanding of dark energy and dark matter. The LSST Dark Energy Science Collabo…

astro-ph.IM2018

Optimizing the LSST Observing Strategy for Dark Energy Science: DESC Recommendations for the Deep Drilling Fields and other Special Programs

Daniel M. Scolnic, Michelle Lochner, Phillipe Gris +21

We review the measurements of dark energy enabled by observations of the Deep Drilling Fields and the optimization of survey design for cosmological measurements. This white paper…

astro-ph.IM2018★ 16 cited

Classification of Multiwavelength Transients with Machine Learning

K. Sooknunan, M. Lochner, Bruce A. Bassett +7

With the advent of powerful telescopes such as the Square Kilometer Array and the Vera C. Rubin Observatory, we are entering an era of multiwavelength transient astronomy that will…

astro-ph.IM2018★ 25 cited

The Photometric LSST Astronomical Time-series Classification Challenge (PLAsTiCC): Selection of a performance metric for classification probabilities balancing diverse science goals

A. I. Malz, R. Hložek, T. Allam +22

Classification of transient and variable light curves is an essential step in using astronomical observations to develop an understanding of their underlying physical processes. Ho…

astro-ph.IM2018★ 53 cited

DeepSource: Point Source Detection using Deep Learning

A. Vafaei Sadr, Etienne. E. Vos, Bruce A. Bassett +3

Point source detection at low signal-to-noise is challenging for astronomical surveys, particularly in radio interferometry images where the noise is correlated. Machine learning i…

astro-ph.IM2018★ 9 cited

Radio Galaxy Shape Measurement with Hamiltonian Monte Carlo in the Visibility Domain

M. Rivi, M. Lochner, S. T. Balan +2

Radio weak lensing, while a highly promising complementary probe to optical weak lensing, will require incredible precision in the measurement of galaxy shape parameters. In this p…