81 citations · 159 across the 4 of their papers we have counts for
4 papers
Jet Diffusion versus JetGPT -- Modern Networks for the LHC
Anja Butter, Nathan Huetsch, Sofia Palacios Schweitzer +3
We introduce two diffusion models and an autoregressive transformer for LHC physics simulations. Bayesian versions allow us to control the networks and capture training uncertainti…
A Normalized Autoencoder for LHC Triggers
Barry M. Dillon, Luigi Favaro, Tilman Plehn +2
Autoencoders are an effective analysis tool for the LHC, as they represent one of its main goal of finding physics beyond the Standard Model. The key challenge is that out-of-distr…
Symmetries, Safety, and Self-Supervision
Barry M. Dillon, Gregor Kasieczka, Hans Olischlager +3
Collider searches face the challenge of defining a representation of high-dimensional data such that physical symmetries are manifest, the discriminating features are retained, and…
Better Latent Spaces for Better Autoencoders
Barry M. Dillon, Tilman Plehn, Christof Sauer +1
Autoencoders as tools behind anomaly searches at the LHC have the structural problem that they only work in one direction, extracting jets with higher complexity but not the other…