Generating variable length full events from partons
This paper presents a novel approach for directly generating full events at detector-level
from parton-level information, leveraging cutting-edge machine learning techniques. To …
from parton-level information, leveraging cutting-edge machine learning techniques. To …
Normalizing Flows for High-Dimensional Detector Simulations
Whenever invertible generative networks are needed for LHC physics, normalizing flows
show excellent performance. A challenge is their scaling to high-dimensional phase spaces …
show excellent performance. A challenge is their scaling to high-dimensional phase spaces …
A portable parton-level event generator for the high-luminosity LHC
The rapid deployment of computing hardware different from the traditional CPU+ RAM
model in data centers around the world mandates a change in the design of event …
model in data centers around the world mandates a change in the design of event …
BUFF: Boosted Decision Tree based Ultra-Fast Flow matching
C Jiang, S Qian, H Qu - arxiv preprint arxiv:2404.18219, 2024 - arxiv.org
Tabular data stands out as one of the most frequently encountered types in high energy
physics. Unlike commonly homogeneous data such as pixelated images, simulating high …
physics. Unlike commonly homogeneous data such as pixelated images, simulating high …
arxiv: Normalizing Flows for High-Dimensional Detector Simulations
F Ernst, L Favaro, T Plehn, D Shih, C Krause - 2023 - cds.cern.ch
Whenever invertible generative networks are needed for LHC physics, normalizing flows
show excellent performance. A challenge is their scaling to high-dimensional phase spaces …
show excellent performance. A challenge is their scaling to high-dimensional phase spaces …
The Flow of LHC Events-Generative models for LHC simulations and inference
T Heimel - 2024 - archiv.ub.uni-heidelberg.de
Generative neural networks have various applications in LHC physics, for both fast
simulations and precise inference. We first show that normalizing flows can be used to …
simulations and precise inference. We first show that normalizing flows can be used to …