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Machine Learning Meets Visualization to Make Artificial Intelligence Interpretable (Dagstuhl Seminar 19452)

Authors: Enrico Bertini, Peer-Timo Bremer, Daniela Oelke, and Jayaraman Thiagarajan

Published in: Dagstuhl Reports, Volume 9, Issue 11 (2020)


Abstract
This report documents the program and the outcomes of Dagstuhl Seminar 19452 "Machine Learning Meets Visualization to Make Artificial Intelligence Interpretable".

Cite as

Enrico Bertini, Peer-Timo Bremer, Daniela Oelke, and Jayaraman Thiagarajan. Machine Learning Meets Visualization to Make Artificial Intelligence Interpretable (Dagstuhl Seminar 19452). In Dagstuhl Reports, Volume 9, Issue 11, pp. 24-33, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2020)


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@Article{bertini_et_al:DagRep.9.11.24,
  author =	{Bertini, Enrico and Bremer, Peer-Timo and Oelke, Daniela and Thiagarajan, Jayaraman},
  title =	{{Machine Learning Meets Visualization to Make Artificial Intelligence Interpretable (Dagstuhl Seminar 19452)}},
  pages =	{24--33},
  journal =	{Dagstuhl Reports},
  ISSN =	{2192-5283},
  year =	{2020},
  volume =	{9},
  number =	{11},
  editor =	{Bertini, Enrico and Bremer, Peer-Timo and Oelke, Daniela and Thiagarajan, Jayaraman},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/DagRep.9.11.24},
  URN =		{urn:nbn:de:0030-drops-119820},
  doi =		{10.4230/DagRep.9.11.24},
  annote =	{Keywords: Visualization, Machine Learning, Interpretability}
}
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