47 citations · 75 across the 6 of their papers we have counts for
3 papers · 1 filter
Anomaly detection with flow-based fast calorimeter simulators
Claudius Krause, Benjamin Nachman, Ian Pang +2
Recently, several normalizing flow-based deep generative models have been proposed to accelerate the simulation of calorimeter showers. Using CaloFlow as an example, we show that t…
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…
Fast Parameter Inference on Pulsar Timing Arrays with Normalizing Flows
David Shih, Marat Freytsis, Stephen R. Taylor +2
Pulsar timing arrays (PTAs) perform Bayesian posterior inference with expensive MCMC methods. Given a dataset of ~10-100 pulsars and O(10^3) timing residuals each, producing a post…