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Particle Track Reconstruction Based on Deep Neural Networks
Particle track reconstruction based on deep learning methods -
ATLAS Experiment at the CERN Large Hadron Collider
ATLAS experiment data -
Dimuon resonance search dataset
The dataset used for testing the β-parameterized VAE for event compression in particle physics experiments. -
Simulated Standard Model events
The dataset used for training and testing the β-parameterized Variational Autoencoder (VAE) for event compression in particle physics experiments. -
PC-JeDi: Particle Cloud Jets with Diffusion
A new method to efficiently generate jets in High Energy Physics called PC-JeDi. This method utilises score-based diffusion models in conjunction with transformers which are... -
JetNet dataset
The JetNet dataset is a benchmark dataset for jet generative modeling, containing features such as kinematics and particle identification. -
JetClass dataset
The JetClass dataset is a large-scale dataset for deep learning in jet physics, containing features such as particle-ID, charge, and trajectory displacement. -
HEP dataset
The dataset contains nearly 300,000 simulated responses, each with 44x44 dimension, and includes nine properties for each particle: momentum and velocity in three planes, as... -
Flavours of Physics: Finding τ → µµµ
The dataset used in this work were provided by Flavours of Physics: Finding τ → µµµ competition on Kaggle. The dataset is suited for binary-classification with the target labels... -
CMS HGCAL Data
The dataset used in this paper is a high-granularity calorimeter data from the CMS experiment at the CERN Large Hadron Collider.
