HIGHLIGHTS
- What: The authors compare ATAT against the current ALeRCE classifier balanced hierarchical random forest (BHRF) trained on human-engineered features derived from light curves and metadata. For the rest of the paper, the authors call these models ATAT variants since different input combinations can be used.
- Who: Cabrera-Vives G. and collaborators from the Department of Computer Science, Universidad de Concepción, Concepción, European Southern, Karl-Schwarzschild-Strasse, Garching bei München, Germany have published the research work: ATAT: Astronomical Transformer for time series and Tabular data, in the Journal: (JOURNAL) of September/28 . . .
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