Name: Anomaly detection with neural networks
Start: 2020-02-21T09:00:00+01:00
End: 2020-02-21T22:05:00+01:00
Location: Giessen University

- 09:30 → 10:00
  
  Coffee
- 09:55 → 22:05
  Presentations I
  - 09:55
    
    Welcome 5m
    
    Speaker: Jens Sören Lange (JLU Giessen)
    
    lange_einleitung.pdf
  - 10:00
    
    Overview (experimental setup, pixel and clusters, search for rare events with new physics, results from multilayer perceptron, results from self-organizing maps) 40m
    
    Speaker: Katharina Dort (JLU Giessen)
    
    neuroseminar_katharina_dort_022020.pdf
  - 10:40
    
    Understanding the n-dim data (principal components analysis, results from self-organizing maps with transformed input) 25m
    
    Speaker: Stephanie Käs (JLU Giessen)
    
    PXD_Dataset_PCA_SOMS_Stephanie_Kaes.pdf
  - 11:05
    
    Results from Hopfield networks 25m
    
    Speaker: Irina Heinz (JLU Giessen)
    
    HopfieldNetwork.pdf
  - 11:30
    
    Convolutional networks 30m
    
    Speaker: Klaus Rinn (THM)
    
    MEK_NN.pdf
  - 12:00
    
    Self-organizing maps 30m
    
    Speaker: Marc Strickert (JLU Giessen)
    
    20200221_strickert_nngi.pdf
- 12:30 → 13:30
  
  Pizza 1h
- 13:30 → 16:00
  Presentations II
  - 13:30
    
    Deep learning applications for the CBM experiment at Fair and the NA61 experiment at CERN 30m
    
    Speaker: Olena Lynnik (JLU Giessen, FIAS, milch&zucker)
    
    21.02.2020.Olena_Linnyk_Giessen.pdf
  - 14:00
    
    Hardware implementation (FPGA, GPU) 30m
    
    Speaker: Jens Sören Lange (JLU Giessen)
    
    lange_hardware.pdf
  - 14:30
    
    Discussion and Wrap-Up 1h 30m

Anomaly detection with neural networks

Chemistry EG 18

Giessen University