6 papers
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…
Diffusion Autoencoders with Perceivers for Long, Irregular and Multimodal Astronomical Sequences
Yunyi Shen, Alexander Gagliano
Self-supervised learning has become a central strategy for representation learning, but the majority of architectures used for encoding data have only been validated on regularly-s…
Hierarchical Simulation-Based Inference of Supernova Power Sources and their Physical Properties
Edgar P. Vidal, Alexander T. Gagliano, Carolina Cuesta-Lazaro
Time domain surveys such as the Vera C. Rubin Observatory are projected to annually discover millions of astronomical transients. This and complementary programs demand fast, autom…
Mixture-of-Expert Variational Autoencoders for Cross-Modality Embedding of Type Ia Supernova Data
Yunyi Shen, Alexander T. Gagliano
Time-domain astrophysics relies on heterogeneous and multi-modal data. Specialized models are often constructed to extract information from a single modality, but this approach ign…
A Wide Field Map of Ultra-Compact Dwarfs in the Coma Cluster
Richard T. Pomeroy, Juan P. Madrid, Conor R. O'Neill +1
A dataset of 23,351 globular clusters (GCs) and ultra-compact dwarfs (UCDs) in the Coma cluster of galaxies was built using Hubble Space Telescope Advanced Camera for Surveys data.…
Variational diffusion transformers for conditional sampling of supernovae spectra
Yunyi Shen, Alexander T. Gagliano
Type Ia Supernovae (SNe Ia) have become the most precise distance indicators in astrophysics due to their incredible observational homogeneity. Increasing discovery rates, however,…