361 citations · 1.2k across the 40 of their papers we have counts for
5 papers · 1 filter
Uncovering Physical Drivers of Dark Matter Halo Structures with Auxiliary-Variable-Guided Generative Models
Arkaprabha Ganguli, Anirban Samaddar, Florian Kéruzoré +4
Deep generative models (DGMs) compress high-dimensional data but often entangle distinct physical factors in their latent spaces. We present an auxiliary-variable-guided framework…
Predicting New Concept-Object Associations in Astronomy by Mining the Literature
Jinchu Li, Yuan-Sen Ting, Alberto Accomazzi +2
We construct a concept-object knowledge graph from the full astro-ph corpus through July 2025. Using an automated pipeline, we extract named astrophysical objects from OCR-processe…
Opportunities in AI/ML for the Rubin LSST Dark Energy Science Collaboration
LSST Dark Energy Science Collaboration, Eric Aubourg, Camille Avestruz +63
The Vera C. Rubin Observatory's Legacy Survey of Space and Time (LSST) will produce unprecedented volumes of heterogeneous astronomical data (images, catalogs, and alerts) that cha…
Emulator-Based Inference of Cosmological Subgrid Models
Nesar Ramachandra, Nicholas Frontiere, Michael Buehlmann +4
The formation of structure in the Universe at large scales is dominated by gravity, with baryonic physics becoming significant at scales. To capture the impact of b…
Multi-task Modeling for Engineering Applications with Sparse Data
Yigitcan Comlek, R. Murali Krishnan, Sandipp Krishnan Ravi +7
Modern engineering and scientific workflows often require simultaneous predictions across related tasks and fidelity levels, where high-fidelity data is scarce and expensive, while…