5 papers
Radiative Transfer Modeling of Stripped-envelope Supernovae II: Neural Network Emulation of Light Curves
S. Karthik Yadavalli, V. Ashley Villar, Maria R. Drout +3
We present the first neural-network emulator of stripped-envelope supernova (SESN) lightcurves, trained on a grid of 4499 light curves simulated with the radiative transfer (RT) co…
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…
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…
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,…