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May 8 – 12, 2023
Norfolk Waterside Marriott
US/Eastern timezone

DeepTreeGAN: Fast Generation of High Dimensional Point Clouds

Not scheduled
1h
Hampton Roads Ballroom and Foyer Area (Norfolk Waterside Marriott)

Hampton Roads Ballroom and Foyer Area

Norfolk Waterside Marriott

235 East Main Street Norfolk, VA 23510
Poster Poster Poster Session

Speaker

Scham, Moritz (Deutsches Elektronen-Synchrotron (DESY))

Description

In High Energy Physics, detailed and time-consuming simulations are used for particle interactions with detectors. To bypass these simulations with a generative model, the generation of large point clouds in a short time is required, while the complex dependencies between the particles must be correctly modeled. Particle showers are inherently tree-based processes, as each particle is produced by decays or detector interaction of a particle of the previous generation.

In this work, we present a novel GNN model that is able to generate such point clouds in a tree-based manner. We show that this model can reproduce complex distributions, and we evaluate its performance on the public JetNet Dataset.

Consider for long presentation No

Primary authors

Scham, Moritz (Deutsches Elektronen-Synchrotron (DESY)) Mr Krücker, Dirk (Deutsches Elektronen-Synchrotron (DESY))

Presentation materials

Peer reviewing

Paper