1.5k citations · 25.1k across the 213 of their papers we have counts for
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AstroLLaMA: Towards Specialized Foundation Models in Astronomy
Tuan Dung Nguyen, Yuan-Sen Ting, Ioana Ciucă +21
Large language models excel in many human-language tasks but often falter in highly specialized domains like scholarly astronomy. To bridge this gap, we introduce AstroLLaMA, a 7-b…
Using transfer learning to detect galaxy mergers
Sandro Ackermann, Kevin Schawinski, Ce Zhang +2
We investigate the use of deep convolutional neural networks (deep CNNs) for automatic visual detection of galaxy mergers. Moreover, we investigate the use of transfer learning in…
Radio Galaxy Zoo: ClaRAN - A Deep Learning Classifier for Radio Morphologies
Chen Wu, O. Ivy Wong, Lawrence Rudnick +13
The upcoming next-generation large area radio continuum surveys can expect tens of millions of radio sources, rendering the traditional method for radio morphology classification t…
Generative Adversarial Networks recover features in astrophysical images of galaxies beyond the deconvolution limit
Kevin Schawinski, Ce Zhang, Hantian Zhang +2
Observations of astrophysical objects such as galaxies are limited by various sources of random and systematic noise from the sky background, the optical system of the telescope an…
Galaxy Zoo: Morphological Classification and Citizen Science
Lucy Fortson, Karen Masters, Robert Nichol +6
We provide a brief overview of the Galaxy Zoo and Zooniverse projects, including a short discussion of the history of, and motivation for, these projects as well as reviewing the s…
Galaxy Zoo Supernovae
A. M. Smith, S. Lynn, M. Sullivan +21
This paper presents the first results from a new citizen science project: Galaxy Zoo Supernovae. This proof of concept project uses members of the public to identify supernova cand…