GalCatDiff applies category embeddings and a novel Astro-RAB block inside diffusion models to produce galaxy images whose color and size distributions match observations more closely than prior generative approaches.
and Driver, Simon P
2 Pith papers cite this work, alongside 94 external citations. Polarity classification is still indexing.
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MtFAD plus MOBSynC on GAMA data yields eight simple clusters that merge into red and blue sequences containing substructure tied to mass quenching, environmental quenching, morphology and environment.
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Category-based Galaxy Image Generation via Diffusion Models
GalCatDiff applies category embeddings and a novel Astro-RAB block inside diffusion models to produce galaxy images whose color and size distributions match observations more closely than prior generative approaches.
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Multi-layered model-based characterisation of the local-Universe galaxy data from the GAMA survey
MtFAD plus MOBSynC on GAMA data yields eight simple clusters that merge into red and blue sequences containing substructure tied to mass quenching, environmental quenching, morphology and environment.