17 citations · 18 across the 3 of their papers we have counts for
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hep-ph2024★ 1 cited
Product Manifold Machine Learning for Physics
Nathaniel S. Woodward, Sang Eon Park, Gaia Grosso +2
Physical data are representations of the fundamental laws governing the Universe, hiding complex compositional structures often well captured by hierarchical graphs. Hyperbolic spa…
hep-ph2024★ 17 cited
Re-Simulation-based Self-Supervised Learning for Pre-Training Foundation Models
Philip Harris, Michael Kagan, Jeffrey Krupa +2
Self-Supervised Learning (SSL) is at the core of training modern large machine learning models, providing a scheme for learning powerful representations that can be used in a varie…