Probabilistic Data-Driven Modelling of Astrophysical Transients: The Neural Process Family for Ultrafast and Class-Agnostic Light Curve Reconstruction with NightLANP

ArXi:2605.27527v1 Announce Type: cross Astrophysical observations taken from Earth are subject to weather, environmental, and scientific constraints that lead to sparse, irregular light curves. On the eve of the Vera C. Rubin Observatory Legacy Survey of Space and Time, its massive dataset offers unprecedented opportunities for transient science. Yet, a key challenge remains its cadence, which will be sparse and irregular across six bands, limiting scientific inference.