Learning representations of irregular particle-detector geometry with distance-weighted graph networks

This publication has 31 references indexed in Scilit:

• FCC-hh: The Hadron Collider
  The European Physical Journal Special Topics, 2019
• Detector Monitoring with Artificial Neural Networks at the CMS Experiment at the CERN Large Hadron Collider
  Computing and Software for Big Science, 2019
• Deep Learning and Its Application to LHC Physics
  Annual Review of Nuclear and Particle Science, 2018
• Machine learning at the energy and intensity frontiers of particle physics
  Nature, 2018
• ImageNet classification with deep convolutional neural networks
  Communications of the ACM, 2017
• Studies of boosted decision trees for MiniBooNE particle identification
  Nuclear Instruments and Methods in Physics Research Section A: Accelerators, Spectrometers, Detectors and Associated Equipment, 2005
• Neural networks in high energy physics: A ten year perspective
  Computer Physics Communications, 1999
• Classification of the hadronic decays of the Z0 into b and c quark pairs using a neural network
  Physics Letters B, 1992
• Track finding with neural networks
  Nuclear Instruments and Methods in Physics Research Section A: Accelerators, Spectrometers, Detectors and Associated Equipment, 1989
• Neural networks and cellular automata in experimental high energy physics
  Computer Physics Communications, 1988