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

- Coffee
- Presentations I
  - 1
    
    Welcome
    
    Speaker: Jens Sören Lange (JLU Giessen)
    
    lange_einleitung.pdf
  - 2
    
    Overview (experimental setup, pixel and clusters, search for rare events with new physics, results from multilayer perceptron, results from self-organizing maps)
    
    Speaker: Katharina Dort (JLU Giessen)
    
    neuroseminar_katharina_dort_022020.pdf
  - 3
    
    Understanding the n-dim data (principal components analysis, results from self-organizing maps with transformed input)
    
    Speaker: Stephanie Käs (JLU Giessen)
    
    PXD_Dataset_PCA_SOMS_Stephanie_Kaes.pdf
  - 4
    
    Results from Hopfield networks
    
    Speaker: Irina Heinz (JLU Giessen)
    
    HopfieldNetwork.pdf
  - 5
    
    Convolutional networks
    
    Speaker: Klaus Rinn (THM)
    
    MEK_NN.pdf
  - 6
    
    Self-organizing maps
    
    Speaker: Marc Strickert (JLU Giessen)
    
    20200221_strickert_nngi.pdf
- 12:30
  
  Pizza
- Presentations II
  - 7
    
    Deep learning applications for the CBM experiment at Fair and the NA61 experiment at CERN
    
    Speaker: Olena Lynnik (JLU Giessen, FIAS, milch&zucker)
    
    21.02.2020.Olena_Linnyk_Giessen.pdf
  - 8
    
    Hardware implementation (FPGA, GPU)
    
    Speaker: Jens Sören Lange (JLU Giessen)
    
    lange_hardware.pdf
  - 9
    
    Discussion and Wrap-Up

Anomaly detection with neural networks

Chemistry EG 18

Giessen University