Photometry-only classification of SNe Ia and Ibc reaches >=90% accuracy by fitting a semi-analytical decay model to light curves and using GMMs on the resulting parameter distributions to estimate mixing fractions without any labeled training data.
Title resolution pending
2 Pith papers cite this work. Polarity classification is still indexing.
2
Pith papers citing it
fields
astro-ph.IM 2years
2026 2representative citing papers
ORACLE-2 multimodal classifiers raise macro F1 from 0.52-0.66 (light-curve only) to 0.73 on ZTF Bright Transient Survey data and reach 0.88 on simulated ELAsTiCC data.
citing papers explorer
-
Photometry is all you need: supernova classification as a mixing problem
Photometry-only classification of SNe Ia and Ibc reaches >=90% accuracy by fitting a semi-analytical decay model to light curves and using GMMs on the resulting parameter distributions to estimate mixing fractions without any labeled training data.