240 citations · 2.4k across the 55 of their papers we have counts for
20 papers · 1 filter
Fast Particle-based Anomaly Detection Algorithm with Variational Autoencoder
Ryan Liu, Abhijith Gandrakota, Jennifer Ngadiuba +2
Model-agnostic anomaly detection is one of the promising approaches in the search for new beyond the standard model physics. In this paper, we present Set-VAE, a particle-based var…
Efficient and Robust Jet Tagging at the LHC with Knowledge Distillation
Ryan Liu, Abhijith Gandrakota, Jennifer Ngadiuba +2
The challenging environment of real-time data processing systems at the Large Hadron Collider (LHC) strictly limits the computational complexity of algorithms that can be deployed.…
Graph Neural Network for Object Reconstruction in Liquid Argon Time Projection Chambers
V Hewes, Adam Aurisano, Giuseppe Cerati +14
This paper presents a graph neural network (GNN) technique for low-level reconstruction of neutrino interactions in a Liquid Argon Time Projection Chamber (LArTPC). GNNs are still…
Angular analysis of the decay B K(892) in proton-proton collisions at 8 TeV
CMS Collaboration
Angular distributions of the decay B K(892) are studied using events collected with the CMS detector in 8 TeV proton-proton collisions at the L…
Graph Neural Networks in Particle Physics
Jonathan Shlomi, Peter Battaglia, Jean-Roch Vlimant
Particle physics is a branch of science aiming at discovering the fundamental laws of matter and forces. Graph neural networks are trainable functions which operate on graphs---set…
Adversarially Learned Anomaly Detection on CMS Open Data: re-discovering the top quark
Oliver Knapp, Guenther Dissertori, Olmo Cerri +3
We apply an Adversarially Learned Anomaly Detection (ALAD) algorithm to the problem of detecting new physics processes in proton-proton collisions at the Large Hadron Collider. Ano…