GANs for generating EFT models

DOI10.1016/j.physletb.2020.135798zbMath1472.81155arXiv1809.02612OpenAlexW2889983866MaRDI QIDQ823097

Harold Erbin, Sven Krippendorf

Publication date: 24 September 2021

Published in: Physics Letters. B (Search for Journal in Brave)

Full work available at URL: https://arxiv.org/abs/1809.02612

Mathematics Subject Classification ID

Learning and adaptive systems in artificial intelligence (68T05) Supersymmetric field theories in quantum mechanics (81T60) Networks and circuits as models of computation; circuit complexity (68Q06) Effective quantum field theories (81T12)

Related Items (6)

Data science applications to string theory ⋮ Machine Learning Line Bundle Cohomology ⋮ Bounding the Kreuzer‐Skarke Landscape ⋮ Machine learning line bundle cohomologies of hypersurfaces in toric varieties ⋮ Branes with brains: exploring string vacua with deep reinforcement learning ⋮ Learning to inflate. A gradient ascent approach to random inflation

Cites Work

• On the geometry of the string landscape and the swampland
• D-branes at singularities: A bottom-up approach to the string embedding of the standard model

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