196 citations · 1.2k across the 21 of their papers we have counts for
22 papers
Learning the language of QCD jets with transformers
Thorben Finke, Michael Krämer, Alexander Mück +1
Transformers have become the primary architecture for natural language processing. In this study, we explore their use for auto-regressive density estimation in high-energy jet phy…
Boosting mono-jet searches with model-agnostic machine learning
Thorben Finke, Michael Krämer, Maximilian Lipp +1
We show how weakly supervised machine learning can improve the sensitivity of LHC mono-jet searches to new physics models with anomalous jet dynamics. The Classification Without La…
What's Anomalous in LHC Jets?
Thorsten Buss, Barry M. Dillon, Thorben Finke +5
Searches for anomalies are a significant motivation for the LHC and help define key analysis steps, including triggers. We discuss specific examples how LHC anomalies can be define…
Autoencoders for unsupervised anomaly detection in high energy physics
Thorben Finke, Michael Krämer, Alessandro Morandini +2
Autoencoders are widely used in machine learning applications, in particular for anomaly detection. Hence, they have been introduced in high energy physics as a promising tool for…
PROPHECY4F 3.0: A Monte Carlo program for Higgs-boson decays into four-fermion final states in and beyond the Standard Model
Ansgar Denner, Stefan Dittmaier, Alexander Mück
The Monte Carlo generator PPROPHECY4F provides a PROPer description of the Higgs dECaY into 4 Fermions within the Standard Model, the Standard Model with a fourth fermion generatio…
Probing Higgs-portal dark matter with vector-boson fusion
Jan Heisig, Michael Krämer, Eric Madge +1
We constrain the Higgs-portal model employing the vector-boson fusion channel at the LHC. In particular, we include the phenomenologically interesting parameter region near the Hig…