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20242026
most citedORACLE: A Real-Time, Hierarchical, Deep-Learning Photometric Classifier for the LSST

7 citations · 12 across the 10 of their papers we have counts for

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astro-ph.IM2026

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,…

astro-ph.IM2026

SELDON: Supernova Explosions Learned by Deep ODE Networks

Jiezhong Wu, Jack O'Brien, Jennifer Li +6

The discovery rate of optical transients will explode to 10 million public alerts per night once the Vera C. Rubin Observatory's Legacy Survey of Space and Time comes online, overw…

astro-ph.IM2026

Opportunities in AI/ML for the Rubin LSST Dark Energy Science Collaboration

LSST Dark Energy Science Collaboration, Eric Aubourg, Camille Avestruz +63

The Vera C. Rubin Observatory's Legacy Survey of Space and Time (LSST) will produce unprecedented volumes of heterogeneous astronomical data (images, catalogs, and alerts) that cha…

astro-ph.IM2025

ORACLE: A Real-Time, Hierarchical, Deep-Learning Photometric Classifier for the LSST

Ved G. Shah, Alex Gagliano, Konstantin Malanchev +3

We present ORACLE, the first hierarchical deep-learning model for real-time, context-aware classification of transient and variable astrophysical phenomena. ORACLE is a recurrent n…

astro-ph.IM2024

Rubin ToO 2024: Envisioning the Vera C. Rubin Observatory LSST Target of Opportunity program

Igor Andreoni, Raffaella Margutti, John Banovetz +86

The Legacy Survey of Space and Time (LSST) at Vera C. Rubin Observatory is planned to begin in the Fall of 2025. The LSST survey cadence has been designed via a community-driven pr…