15 citations · 29 across the 4 of their papers we have counts for
5 papers
The Rubin Observatory Target-of-Opportunity System in the First Year of Operations
Sean Patrick MacBride, R. Lynne Jones, Peter Yoachim +41
The NSF/DOE Vera C. Rubin Observatory is a discovery machine, with unprecedented survey speed, which can be used to identify exotic astrophysical transients. In its prime mission,…
The Vera C. Rubin Observatory Data Preview 1
Vera C Rubin Observatory Team, Tatiana Acero Cuellar, Emily Acosta +325
We present Rubin Data Preview 1 DP1, the first data from the NSF DOE Vera C Rubin Observatory, comprising raw and calibrated single epoch images, coadds, difference images, detecti…
Transformer-Based Neural Network for Transient Detection without Image Subtraction
Adi Inada, Masao Sako, Tatiana Acero-Cuellar +1
We introduce a transformer-based neural network for the accurate classification of real and bogus transient detections in astronomical images. This network advances beyond the conv…
Toward automated detection of light echoes in synoptic surveys: considerations on the application of the Deep Convolutional Neural Networks
Xiaolong Li, Federica B. Bianco, Gregory Dobler +7
Light Echoes (LEs) are the reflections of astrophysical transients off of interstellar dust. They are fascinating astronomical phenomena that enable studies of the scattering dust…
What's the Difference? The potential for Convolutional Neural Networks for transient detection without template subtraction
Tatiana Acero-Cuellar, Federica Bianco, Gregory Dobler +3
We present a study of the potential for Convolutional Neural Networks (CNNs) to enable separation of astrophysical transients from image artifacts, a task known as "real-bogus" cla…