Jet Tagging

16 papers with code • 1 benchmarks • 1 datasets

Jet tagging is the process of identifying the type of elementary particle that initiates a "jet", i.e., a collimated spray of outgoing particles. It is essentially a classification task that aims to distinguish jets arising from particles of interest, such as the Higgs boson or the top quark, from other less interesting types of jets.


Use these libraries to find Jet Tagging models and implementations


Most implemented papers

ParticleNet: Jet Tagging via Particle Clouds

hqucms/weaver-core 22 Feb 2019

How to represent a jet is at the core of machine learning on jet physics.

Gradient-based Automatic Per-Weight Mixed Precision Quantization for Neural Networks On-Chip

calad0i/HGQ 1 May 2024

Model size and inference speed at deployment time, are major challenges in many deep learning applications.

Jet-Images -- Deep Learning Edition

deepjets/deepjets 16 Nov 2015

Building on the notion of a particle physics detector as a camera and the collimated streams of high energy particles, or jets, it measures as an image, we investigate the potential of machine learning techniques based on deep learning architectures to identify highly boosted W bosons.

Variational Autoencoders for Anomalous Jet Tagging

taolicheng/VAE-Jet 3 Jul 2020

To build a performant mass-decorrelated anomalous jet tagger, we propose the Outlier Exposed VAE (OE-VAE), for which some outlier samples are introduced in the training process to guide the learned information.

Jet tagging in the Lund plane with graph networks

fdreyer/LundNet 15 Dec 2020

The identification of boosted heavy particles such as top quarks or vector bosons is one of the key problems arising in experimental studies at the Large Hadron Collider.

Point Cloud Transformers applied to Collider Physics

ViniciusMikuni/PCT_HEP 9 Feb 2021

Methods for processing point cloud information have seen a great success in collider physics applications.

Particle Transformer for Jet Tagging

jet-universe/particle_transformer 8 Feb 2022

Based on the large dataset, we propose a new Transformer-based architecture for jet tagging, called Particle Transformer (ParT).

Improving Robustness of Jet Tagging Algorithms with Adversarial Training

AnnikaStein/Adversarial-Training-for-Jet-Tagging 25 Mar 2022

We investigate the classifier response to input data with injected mismodelings and probe the vulnerability of flavor tagging algorithms via application of adversarial attacks.

BIP: Boost Invariant Polynomials for Efficient Jet Tagging

ACEsuit/BIPs.jl 17 Jul 2022

Deep Learning approaches are becoming the go-to methods for data analysis in High Energy Physics (HEP).

Do graph neural networks learn traditional jet substructure?

farakiko/xai4hep 17 Nov 2022

At the CERN LHC, the task of jet tagging, whose goal is to infer the origin of a jet given a set of final-state particles, is dominated by machine learning methods.