3 papers
hep-ph2026
Look everywhere effects in anomaly detection
Marie Hein, Benjamin Nachman, David Shih
Machine learning-based anomaly detection methods are able to search high-dimensional spaces for hints of new physics with much less theory bias than traditional searches. However,…
hep-ph2025
Unifying Simulation and Inference with Normalizing Flows
Haoxing Du, Claudius Krause, Vinicius Mikuni +3
There have been many applications of deep neural networks to detector calibrations and a growing number of studies that propose deep generative models as automated fast detector si…
hep-ph2025
Normalizing Flows for High-Dimensional Detector Simulations
Florian Ernst, Luigi Favaro, Claudius Krause +2
Whenever invertible generative networks are needed for LHC physics, normalizing flows show excellent performance. In this work, we investigate their performance for fast calorimete…