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Found 3 papers, 3 papers with code
The Tiny Time-series Transformer: Low-latency High-throughput Classification of Astronomical Transients using Deep Model Compression
We also show that in addition to the deep compression techniques, careful choice of file formats can improve inference latency, and thereby throughput of alerts, on the order of $8\times$ for local processing, and $5\times$ in a live production setting.
Paying Attention to Astronomical Transients: Introducing the Time-series Transformer for Photometric Classification
Recent efforts have sought to leverage machine learning methods to tackle the challenge of astronomical transient classification, with ever improving success.
The Photometric LSST Astronomical Time-series Classification Challenge (PLAsTiCC): Data set
The Photometric LSST Astronomical Time Series Classification Challenge (PLAsTiCC) is an open data challenge to classify simulated astronomical time-series data in preparation for observations from the Large Synoptic Survey Telescope (LSST), which will achieve first light in 2019 and commence its 10-year main survey in 2022.
Instrumentation and Methods for Astrophysics Solar and Stellar Astrophysics
