JetClass: A Large-Scale Dataset for Deep Learning in Jet Physics
<p>JetClass is a new large-scale dataset to facilitate deep learning research in jet physics. It consists of 100M jets for training, 5M for validation and 20M for testing. The dataset contains 10 classes of jets, simulated with MadGraph + Pythia + Delphes. <br> <br> A detailed description of the JetClass dataset is presented in the paper <a href="https://arxiv.org/abs/2202.03772">Particle Transformer for Jet Tagging</a>. An interface to use the dataset is provided in <a href="https://github.com/jet-universe/particle_transformer">https://github.com/jet-universe/particle_transformer</a>.</p>
ShareScore
40/100
Overall dataset sharing score
Score breakdown
These five areas show where the dataset supports — or may limit — practical reuse.
- Stewardship
- 8
- Harmonization
- 4
- Access
- 16
- Reuse readiness
- 8
- Engagement
- 4