9 citations · 14 across the 5 of their papers we have counts for
5 papers
How DREAMS are made: Emulating Satellite Galaxy and Subhalo Populations with Diffusion Models and Point Clouds
Tri Nguyen, Francisco Villaescusa-Navarro, Siddharth Mishra-Sharma +16
The connection between galaxies and their host dark matter (DM) halos is critical to our understanding of cosmology, galaxy formation, and DM physics. To maximize the return of upc…
Maven: A Multimodal Foundation Model for Supernova Science
Gemma Zhang, Thomas Helfer, Alexander T. Gagliano +2
A common setting in astronomy is the availability of a small number of high-quality observations, and larger amounts of either lower-quality observations or synthetic data from sim…
Low-Budget Simulation-Based Inference with Bayesian Neural Networks
Arnaud Delaunoy, Maxence de la Brassinne Bonardeaux, Siddharth Mishra-Sharma +1
Simulation-based inference methods have been shown to be inaccurate in the data-poor regime, when training simulations are limited or expensive. Under these circumstances, the infe…
PAPERCLIP: Associating Astronomical Observations and Natural Language with Multi-Modal Models
Siddharth Mishra-Sharma, Yiding Song, Jesse Thaler
We present PAPERCLIP (Proposal Abstracts Provide an Effective Representation for Contrastive Language-Image Pre-training), a method which associates astronomical observations image…
Inferring subhalo effective density slopes from strong lensing observations with neural likelihood-ratio estimation
Gemma Zhang, Siddharth Mishra-Sharma, Cora Dvorkin
Strong gravitational lensing has emerged as a promising approach for probing dark matter models on sub-galactic scales. Recent work has proposed the subhalo effective density slope…