3 citations · 8 across the 15 of their papers we have counts for
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astro-ph.IM2023★ 3 cited
A Physics-Informed Variational Autoencoder for Rapid Galaxy Inference and Anomaly Detection
Alexander Gagliano, V. Ashley Villar
The Vera C. Rubin Observatory is slated to observe nearly 20 billion galaxies during its decade-long Legacy Survey of Space and Time. The rich imaging data it collects will be an i…
astro-ph.IM2023★ 1 cited
Hierarchical Cross-entropy Loss for Classification of Astrophysical Transients
V. Ashley Villar, Kaylee de Soto, Alex Gagliano
Astrophysical transient phenomena are traditionally classified spectroscopically in a hierarchical taxonomy; however, this graph structure is currently not utilized in neural net-b…
astro-ph.IM2023★ 2 cited
Constructing Impactful Machine Learning Research for Astronomy: Best Practices for Researchers and Reviewers
D. Huppenkothen, M. Ntampaka, M. Ho +19
Machine learning has rapidly become a tool of choice for the astronomical community. It is being applied across a wide range of wavelengths and problems, from the classification of…