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A Graph Attention Network Framework for Simultaneous Prediction of Galaxy and Dark Matter Halo Properties in GAMA DR4
We develop a graph-based deep learning model, GAMANet, to predict galaxy and halo properties using the GAMA DR4 dataset. Multiple catalogues are combined to construct a unified sample of 19,469 galaxies and derive a set of photometric, spectroscopic, morphological, and environmental features. The ga
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