Conveners
Architectures
- Matthew Schwartz
- Taoli Cheng (University of Montreal)
Convolutional Neural Networks are an important tool for image classification both in and outside of particle physics. Capsule networks allow us to expand on the standard CNNs setup, both to increase the networks performance and to give insight into its decision making processes. We demonstrate the use of the Capsule Networks by separating a resonance decaying to top quarks from both, QCD...
Quark-gluon tagging refers to the task of identifying the origin of a jet as produced from the hadronization of a gluon or a quark. Common methods rely on jet constituent properties to disentangle the two objects to varying degrees of success. In this talk an innovative method of classifying jets according to its constituents is introduced. The method uses the information of the constituents...
Deciphering the complex information contained in jets produced in collider events requires a physical organization of the jet data. In this talk I will discuss the use of two-particle correlations (2PCs) by pairing individual particles as the initial jet representation from which a probabilistic model can be built. Particle momenta, as well as particle types and vertex information are included...