3 citations · 8 across the 15 of their papers we have counts for
7 papers · 1 filter
Minuet: A Diffusion Autoencoder for Compact Semantic Compression of Multi-Band Galaxy Images
Alexander T. Gagliano, Yunyi Shen, V. A. 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…
reLAISS: A Python Package for Flexible Similarity Searches of Supernovae and Their Host Galaxies
E. Reynolds, A. Gagliano, V. A. Villar
Discovery rates of supernovae are expected to surpass one million events annually with the Vera C. Rubin Observatory. With unprecedented sample sizes of both common and rare transi…
A Poisson Process AutoDecoder for X-ray Sources
Yanke Song, Victoria Ashley Villar, Juan Rafael Martinez-Galarza +1
X-ray observing facilities, such as the Chandra X-ray Observatory and the eROSITA, have detected millions of astronomical sources associated with high-energy phenomena. The arrival…
Off-axis Hartmann wavefront sensing for the GMT-Consortium Large Earth Finder (G-CLEF) red camera optics
Matthew C. H. Leung, Colby A. Jurgenson, Andrew Szentgyorgyi +10
The Hartmann test is a method used to measure the wavefront error in a focal optical system, wherein a mask with a pattern of small holes is placed at the system's aperture stop. B…
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…
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…
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…