Researchers developed a dual-encoder framework that separates intrinsic signals of celestial objects from sensor artifacts. Using counterfactual generation on overlapping galaxy images enhances astrophysical insights and comparisons across instruments. https://arxiv.org/abs/2604.09787
ArXiv link for Learning What's Real: Disentangling Signal and Measurement Artifacts in Multi-Sensor Data, with Applications to Astrophysics
