ASTROCO: Self-Supervised Conformer-Style Transformers for Light-Curve Embeddings
Antony Tan, Pavlos Protopapas, Martina Cádiz-Leyton, Guillermo Cabrera-Vives, Cristobal Donoso-Oliva, Ignacio Becker
公開日: 2025/9/29
Abstract
We present AstroCo, a Conformer-style encoder for irregular stellar light curves. By combining attention with depthwise convolutions and gating, AstroCo captures both global dependencies and local features. On MACHO R-band, AstroCo outperforms Astromer v1 and v2, yielding 70 percent and 61 percent lower error respectively and a relative macro-F1 gain of about 7 percent, while producing embeddings that transfer effectively to few-shot classification. These results highlight AstroCo's potential as a strong and label-efficient foundation for time-domain astronomy.