DeepTreeGANv2: Iterative Pooling of Point Clouds
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Abstract (arXiv)
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 modelled. Particle showers are inherently tree-based processes, as each particle is produced by the decay or detector interaction of a particle of the previous generation. In this work, we present a significant extension to DeepTreeGAN, featuring a critic, that is able to aggregate such point clouds iteratively in a tree-based manner. We show that this model can reproduce complex distributions, and we evaluate its performance on the public JetNet 150 dataset.
Key facts. Cited by 2 papers in the map (data through 7 Oct 2026). Builds on 21 of its 44 references that are in the map. First posted on arXiv 24 Nov 2023.
Builds on
21 of 44 references.
References · 21
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9 more
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Citing papers per year: 2024: 1; 2025: 1.
2 papers.