Attentive Neural Processes outperform Gaussian Processes and neural networks on light curve interpolation quality, feature recovery, calibration, and speed for 15 transient classes under realistic Rubin cadences.
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2026 2verdicts
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A meta-learning framework with ALNP, SOM clustering, and mixture density models improves AGN light-curve reconstruction by 60-70% and parameter recovery on simulated and ZTF data.
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Probabilistic Data-Driven Modelling of Astrophysical Transients: The Neural Process Family for Ultrafast and Class-Agnostic Light Curve Reconstruction with NightLANP
Attentive Neural Processes outperform Gaussian Processes and neural networks on light curve interpolation quality, feature recovery, calibration, and speed for 15 transient classes under realistic Rubin cadences.
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A Meta-Learning Framework for Multitask Reverberation Mapping in Active Galactic Nuclei
A meta-learning framework with ALNP, SOM clustering, and mixture density models improves AGN light-curve reconstruction by 60-70% and parameter recovery on simulated and ZTF data.