283 citations · 2.1k across the 38 of their papers we have counts for
8 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…
Deep Generative Models for Detector Signature Simulation: A Taxonomic Review
Baran Hashemi, Claudius Krause
In modern collider experiments, the quest to explore fundamental interactions between elementary particles has reached unparalleled levels of precision. Signatures from particle ph…
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…
Combining Resonant and Tail-based Anomaly Detection
Gerrit Bickendorf, Manuel Drees, Gregor Kasieczka +2
In many well-motivated models of the electroweak scale, cascade decays of new particles can result in highly boosted hadronic resonances (e.g. ). This can make these models…
The Interplay of Machine Learning--based Resonant Anomaly Detection Methods
Tobias Golling, Gregor Kasieczka, Claudius Krause +6
Machine learning--based anomaly detection (AD) methods are promising tools for extending the coverage of searches for physics beyond the Standard Model (BSM). One class of AD metho…
How to Understand Limitations of Generative Networks
Ranit Das, Luigi Favaro, Theo Heimel +3
Well-trained classifiers and their complete weight distributions provide us with a well-motivated and practicable method to test generative networks in particle physics. We illustr…
Inductive Simulation of Calorimeter Showers with Normalizing Flows
Matthew R. Buckley, Claudius Krause, Ian Pang +1
Simulating particle detector response is the single most expensive step in the Large Hadron Collider computational pipeline. Recently it was shown that normalizing flows can accele…
L2LFlows: Generating High-Fidelity 3D Calorimeter Images
Sascha Diefenbacher, Engin Eren, Frank Gaede +4
We explore the use of normalizing flows to emulate Monte Carlo detector simulations of photon showers in a high-granularity electromagnetic calorimeter prototype for the Internatio…