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{
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{
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"index":4,
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"index":4,
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"title":"Pixel Attribution",
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"title":"Pixel Attribution",
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"paper":"Deep Inside Convolutional Networks: Visualising Image Classification Models and Saliency Maps",
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"paper":"Efficient Saliency Maps for Explainable AI",
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"chapter":"10.2",
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"chapter":"10.2",
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"by": "Simonyan, Vedaldi, et al.",
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"by": "Mundhenk, Chen, et al.",
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"when": "2013",
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"when": "2019",
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"who": "Simon Klüttermann",
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"who": "Simon Klüttermann",
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"mail": "simon.kluettermann@cs.uni-dortmund.de",
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"mail": "simon.kluettermann@cs.uni-dortmund.de",
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"note1":"Different parts of an image have different effect/importance on the classification of an image",
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"note1":"Different parts of an image have different effect/importance on the classification of an image",
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"note2":"{null}",
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"note2":"Programming task: Generate one Saliency Map yourself!",
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"ext": "jpeg"
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"ext": "jpeg"
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}
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}
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\includegraphics[height=3cm]{illustrations/##name##.##ext##}
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\begin{itemize}
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\item ##note1##
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\item ##note1##
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\item ##note2##
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\item ##note2##
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[0] Config.pm:311> INFO - This is Biber 2.16
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[53] biber:340> INFO - === Do Mär 31, 2022, 16:44:30
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[55] biber:340> INFO - === Fr Apr 1, 2022, 13:12:40
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This is LuaHBTeX, Version 1.13.2 (TeX Live 2021/Arch Linux) (format=lualatex 2022.2.18) 31 MAR 2022 16:44
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\begin{itemize}
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\begin{itemize}
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\item Slight changes in a neural network can change its output drastically
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\item Slight changes in a neural network can change its output drastically
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\item Represent some model output by well fitting data instances
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\item Represent some model output by well fitting data instances
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\item Use game theory to explain the output of a model
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\item Use game theory to explain the output of a model
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\item You could either focus on cs theory or on medical application
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\item You could either focus on cs theory or on medical application
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\begin{frame}
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\frametitle{Topic 4: Pixel Attribution}
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\frametitle{Topic 4: Pixel Attribution}
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\Large \textbf{Deep Inside Convolutional Networks: Visualising Image Classification Models and Saliency Maps} (Simonyan, Vedaldi, et al., 2013)\\
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\Large \textbf{Efficient Saliency Maps for Explainable AI} (Mundhenk, Chen, et al., 2019)\\
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\LARGE \textbf{Chapter:} 10.2 \textbf{Supervisor:} Simon Klüttermann (simon.kluettermann@cs.uni-dortmund.de)\\
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\LARGE \textbf{Chapter:} 10.2 \textbf{Supervisor:} Simon Klüttermann (simon.kluettermann@cs.uni-dortmund.de)\\
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\item Different parts of an image have different effect/importance on the classification of an image
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\item Different parts of an image have different effect/importance on the classification of an image
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\item Programming task: Generate one Saliency Map yourself!
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\end{itemize}
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