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20202026
most citedEvery Datapoint Counts: Stellar Flares as a Case Study of Atmosphere Aided Studies of Transients in the LSST Era

1 citations · 2 across the 7 of their papers we have counts for

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astro-ph.IM2026

How Low Can We Go? Minimum Spectroscopic Requirements For Supernova Subtype Classification

Willow Fox Fortino, Federica B. Bianco, Maryam Modjaz +2

Millions of supernovae will be discovered with the Vera C. Rubin Observatory Legacy Survey of Space and Time (LSST). As a result, spectrographs around the world will have to make d…

astro-ph.IM2026

On the performance of pre-trained vision transformers for supernova spectral classification using different spectral representations

J. Serrano Bell, P. Gálvez Molina, V. Contreras Rojas +4

The spectroscopic classification of supernovae is a key component of time-domain astronomy and plays an important role in the identification of Type Ia events. The increasing volum…

astro-ph.IM2026

Microlensify: a Transformer Based Machine Learning Classifier for Microlensing Events Trained on TESS Light Curves

Atousa Kalantari, Somayeh Khakpash, Sedighe Sajadian +3

Microlensing can reveal populations of faint compact objects that are otherwise difficult to detect. Depending on their design, all-sky surveys have the potential to search for the…

astro-ph.IM2025★ 1 cited

ABC-SN: Attention Based Classifier for Supernova Spectra

Willow Fox Fortino, Federica B. Bianco, Pavlos Protopapas +2

While significant advances have been made in photometric classification ahead of the millions of transient events and hundreds of supernovae (SNe) each night that the Vera C. Rubin…

astro-ph.IM2024★ 1 cited

Every Datapoint Counts: Stellar Flares as a Case Study of Atmosphere Aided Studies of Transients in the LSST Era

Riley W. Clarke, James R. A. Davenport, John Gizis +8

Due to their short timescale, stellar flares are a challenging target for the most modern synoptic sky surveys. The upcoming Vera C. Rubin Legacy Survey of Space and Time (LSST), a…

astro-ph.IM2022

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…