Sign in

Graph Neural Networks for Low-Energy Event Classification & Reconstruction in IceCube.

Rasha U. AbbasiMarkus AckermannJenni AdamsN. AggarwalJ. A. AguilarMarkus AhlersMarkus AhrensJ. M. AlameddineA. A. Alves Jr.N. M. AminK. AndeenTyler AndersonGisela AntonCarlos A. ArgüellesY. AshidaS. AthanasiadouS. AxaniXinhua BaiA. Balagopal V.M. BaricevicSteven W. BarwickVedant BasuRyan BayJames J. BeattyKarl-Heinz BeckerJulia K. Becker TjusJ. BeiseChiara BellenghiS. BendaSegev BenZviDavid BerleyElisa BernardiniDavid Z. BessonG. BinderDaniel BindigErik BlaufussSummer BlotF. BontempoJ. Y. BookJ. BorowkaC. Boscolo MeneguoloSebastian BöserOlga BotnerJakob BöttcherEtienne BourbeauJ. BraunB. BrinsonJannes Brostean-KaiserR. T. BurleyRaffaela S. BusseMichael A. CampanaE. G. Carnie-BroncaChujie ChenZ. ChenDmitry ChirkinK. ChoiB. A. ClarkLew ClassenAlan ColemanGabriel H. CollinA. ConnollyJ. M. Conradet al.
Published in: CoRR (2022)
Keyphrases
  • low energy
  • neural network
  • pattern recognition
  • classification accuracy
  • three dimensional
  • electron microscopy
  • minimum energy
  • real time
  • feature space
  • artificial neural networks
  • low cost
  • multi layer