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Enabling Reproducibility and Meta-learning Through a Lifelong Database of Experiments (LDE)
We present the Lifelong Database of Experiments (LDE) that automatically extracts and stores linked metadata from experiment artifacts and provides features to reproduce these artifacts and perform meta-learning across them.
Galaxy classification: A machine learning analysis of GAMA catalogue data
We present a machine learning analysis of five labelled galaxy catalogues from the Galaxy And Mass Assembly (GAMA): The SersicCatVIKING and SersicCatUKIDSS catalogues containing morphological features, the GaussFitSimple catalogue containing spectroscopic features, the MagPhys catalogue including physical parameters for galaxies, and the Lambdar catalogue, which contains photometric measurements.
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