A comprehensive public dataset of simulated Ariel exoplanet transmission spectra is released to benchmark detrending algorithms, with an ML baseline highlighting dataset shift risks.
Title resolution pending
2 Pith papers cite this work. Polarity classification is still indexing.
2
Pith papers citing it
years
2026 2representative citing papers
Neo, a cGAN, super-resolves HSC images to HST-like quality and improves galaxy morphological parameter accuracy by factors of 2-10.
citing papers explorer
-
A public dataset of Ariel simulated observations for developing exoplanetary atmosphere data reduction pipelines
A comprehensive public dataset of simulated Ariel exoplanet transmission spectra is released to benchmark detrending algorithms, with an ML baseline highlighting dataset shift risks.
-
Photometric Super-Resolution for Improving Galaxy Morphological Measurements using Conditional Generative Adversarial Networks
Neo, a cGAN, super-resolves HSC images to HST-like quality and improves galaxy morphological parameter accuracy by factors of 2-10.