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cs.LG2026★ 2 cited
Uncertainty Quantification in Pairwise Difference Learning for Classification
Mohamed Karim Belaid, Maximilian Rabus, Eyke Hüllermeier
Instead of learning a mapping from instances to outcomes in the standard way, the key idea of pairwise difference learning (PDL) is to learn a function that takes two instances as…
astro-ph.IM2026
Toward decision-aware AI for LSST-scale time-domain astronomy
C. R. Bom, A. Mahabal, F. Bianco +27
The Vera C. Rubin Observatory's Legacy Survey of Space and Time (LSST) will generate approximately (10^7) alerts per night, pushing time-domain astronomy beyond pipelines that trea…