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Anomaly detection with neural networks

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Chemistry EG 18 (Giessen University)

Chemistry EG 18

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
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