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).
Graph Neural Networks for quark/gluon jet tagging using particle-level jet constituents, PyTorch Geometric, and HEP-inspired robustness studies.
PyTorch MLP for boosted W/Z→qq̄ jet tagging on ATLAS Open Data; compares to cuts and outputs ROC/purity plots.
Jet Tagging using graph represenation and MLP/Mamba Mixer
Deep learning pipeline in MATLAB comparing CNN and GraphSAGE for top quark jet tagging, with robustness study under detector noise and explainability analysis.
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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