14 citations · 23 across the 7 of their papers we have counts for
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physics.data-an2023★ 1 cited
Improving new physics searches with diffusion models for event observables and jet constituents
Debajyoti Sengupta, Matthew Leigh, John Andrew Raine +2
We introduce a new technique called Drapes to enhance the sensitivity in searches for new physics at the LHC. By training diffusion models on side-band data, we show how background…
hep-ph2023★ 14 cited
EPiC-ly Fast Particle Cloud Generation with Flow-Matching and Diffusion
Erik Buhmann, Cedric Ewen, Darius A. Faroughy +7
Jets at the LHC, typically consisting of a large number of highly correlated particles, are a fascinating laboratory for deep generative modeling. In this paper, we present two nov…