11 datasets found

Particle track reconstruction based on deep learning methods

ATLAS experiment data

The dataset used for testing the β-parameterized VAE for event compression in particle physics experiments.

The dataset used for training and testing the β-parameterized Variational Autoencoder (VAE) for event compression in particle physics experiments.

A dataset of simulated proton-proton collision events for the ATLAS and CMS experiments.

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...

The JetNet dataset is a benchmark dataset for jet generative modeling, containing features such as kinematics and particle identification.

The JetClass dataset is a large-scale dataset for deep learning in jet physics, containing features such as particle-ID, charge, and trajectory displacement.

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...

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...

The dataset used in this paper is a high-granularity calorimeter data from the CMS experiment at the CERN Large Hadron Collider.