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astro-ph.IM2022★ 38 cited
ASTROMER: A transformer-based embedding for the representation of light curves
C. Donoso-Oliva, I. Becker, P. Protopapas +3
Taking inspiration from natural language embeddings, we present ASTROMER, a transformer-based model to create representations of light curves. ASTROMER was pre-trained in a self-su…
cs.LG2022★ 6 cited
ConDA: Simplifying Semi-supervised Domain Adaptation by Learning Consistent and Contrastive Feature Representations
Manuel Pérez-Carrasco, Pavlos Protopapas, Guillermo Cabrera-Vives
In this work, we present ConDA, a simple framework that extends recent advances in semi-supervised learning to the semi-supervised domain adaptation (SSDA) problem. Our frame…