Official implementation of "Particle Transformer for Jet Tagging".
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Updated
May 13, 2024 - Python
Official implementation of "Particle Transformer for Jet Tagging".
Code for "Improving robustness of jet tagging algorithms with adversarial training" (arXiv:2203.13890).
PyTorch MLP for boosted W/Z→qq̄ jet tagging on ATLAS Open Data; compares to cuts and outputs ROC/purity plots.
Graph Neural Networks for quark/gluon jet tagging using particle-level jet constituents, PyTorch Geometric, and HEP-inspired robustness studies.
Deep learning pipeline in MATLAB comparing CNN and GraphSAGE for top quark jet tagging, with robustness study under detector noise and explainability analysis.
Jet Tagging using graph represenation and MLP/Mamba Mixer
GNN (dynamic k-NN ParticleNet) vs Deep Sets on jet tagging -- an honest report including a negative result on when graph structure does and does not help.
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