User Tools

Site Tools


hepsim:public

Differences

This shows you the differences between two versions of the page.

Link to this comparison view

Next revision
Previous revision
hepsim:public [2024/07/01 21:25] – created - external edit 127.0.0.1hepsim:public [2024/09/27 14:53] (current) hepsim17
Line 1: Line 1:
- 
 {{indexmenu_n>120}} {{indexmenu_n>120}}
 [[:|<< back to HepSim manual]] [[:|<< back to HepSim manual]]
Line 67: Line 66:
   * S.Chekanov, R.Zhang, Enhancing the hunt for new phenomena in dijet final states using anomaly detection filters at the high-luminosity large Hadron Collider, Eur. Phys. J. Plus (2024) 139:237   * S.Chekanov, R.Zhang, Enhancing the hunt for new phenomena in dijet final states using anomaly detection filters at the high-luminosity large Hadron Collider, Eur. Phys. J. Plus (2024) 139:237
   * Machine learning could help reveal undiscovered particles within data from the Large Hadron Collider, 2024, April  [[https://www.anl.gov/article/machine-learning-could-help-reveal-undiscovered-particles-within-data-from-the-large-hadron-collider|ANL press release]] [[https://www.newswise.com/doescience/machine-learning-could-help-reveal-undiscovered-particles-within-data-from-the-large-hadron-collider|newswise]] [[https://phys.org/news/2024-04-machine-reveal-undiscovered-particles-large.html|Phys.Org]]   * Machine learning could help reveal undiscovered particles within data from the Large Hadron Collider, 2024, April  [[https://www.anl.gov/article/machine-learning-could-help-reveal-undiscovered-particles-within-data-from-the-large-hadron-collider|ANL press release]] [[https://www.newswise.com/doescience/machine-learning-could-help-reveal-undiscovered-particles-within-data-from-the-large-hadron-collider|newswise]] [[https://phys.org/news/2024-04-machine-reveal-undiscovered-particles-large.html|Phys.Org]]
 +  * ADFilter - a web tool for anomaly detection using autoencoders based on deep unsupervised neural networks, ATL-COM-PHYS-2024-469, July 6, 2024, https://cds.cern.ch/record/2903181
 +  *  * S.V. Chekanov, W. Islam, R. Zhang, N. Luongo, "ADFilter -- A Web Tool for New Physics Searches With Autoencoder-Based Anomaly Detection Using Deep Unsupervised Neural Networks", (September 2024) ANL-HEP-190964, arXiv:2409.03065 (https://arxiv.org/abs/2409.03065)
 +
  
 There are also several ATLAS papers and a number of supporting notes that used Monte Carlo files from the HEPSIM repository. There are also several ATLAS papers and a number of supporting notes that used Monte Carlo files from the HEPSIM repository.
Line 132: Line 134:
   * S.Chekanov, HepSim Monte Carlo repository and integration of its software with key4hep, FCC Software Meeting, May 30, 2023, https://indico.cern.ch/event/1283173/,   * S.Chekanov, HepSim Monte Carlo repository and integration of its software with key4hep, FCC Software Meeting, May 30, 2023, https://indico.cern.ch/event/1283173/,
   * S.Chekanov et al, Geant4 simulations of sampling and homogeneous hadronic calorimeters with dual readout for future colliders, 2nd Future circular collider workshop (FCC-ee), Boston, MIT, March 24-28, 2024, (https://indico.mit.edu/event/876/)   * S.Chekanov et al, Geant4 simulations of sampling and homogeneous hadronic calorimeters with dual readout for future colliders, 2nd Future circular collider workshop (FCC-ee), Boston, MIT, March 24-28, 2024, (https://indico.mit.edu/event/876/)
-  *   S.Chekanov et al, ADFilter: Online tool for processing BSM models using trained deep learning autoencoder. ATLAS Machine Learning Workshop,  May 13-16 (2024). https://indico.cern.ch/event/1352459/overview (CERN). +  *  S.Chekanov et al, ADFilter: Online tool for processing BSM models using trained deep learning autoencoder. ATLAS Machine Learning Workshop,  May 13-16 (2024). https://indico.cern.ch/event/1352459/overview (CERN).  
 +  * S.Chekanov et al, The initial studies of tracking using the CLD detector for FCC-ee. The FCCee detector meeting, CERN, Sep 28,  2024 https://indico.cern.ch/event/1448441/ 
 +   
   
    
      
    
hepsim/public.1719869101.txt.gz · Last modified: 2024/07/01 21:25 by 127.0.0.1