Machine Learning Meets Visualization to Make Artificial Intelligence Interpretable

• Rushil Anirudh (LLNL – Livermore, US) [dblp]
• Enrico Bertini (NYU – Brooklyn, US) [dblp]
• Alexander Binder (Singapore University of Technology and Design, SG) [dblp]
• Peer-Timo Bremer (LLNL – Livermore, US) [dblp]
• Mennatallah El-Assady (Universität Konstanz, DE) [dblp]
• Sorelle Friedler (Haverford College, US) [dblp]
• Beatrice Gobbo (Polytechnic University of Milan, IT)
• Nikou Guennemann (Siemens AG – München, DE) [dblp]
• Nathan Hodas (Pacific Northwest National Lab. – Richland, US) [dblp]
• Daniel A. Keim (Universität Konstanz, DE) [dblp]
• Been Kim (Google Brain – Mountain View, US) [dblp]
• Gordon Kindlmann (University of Chicago, US) [dblp]
• Sebastian Lapuschkin (Fraunhofer-Institut – Berlin, DE) [dblp]
• Heike Leitte (TU Kaiserslautern, DE) [dblp]
• Yao Ming (HKUST – Kowloon, HK) [dblp]
• Elisabeth Moore (Los Alamos National Laboratory, US) [dblp]
• Daniela Oelke (Siemens AG – München, DE) [dblp]
• Steve Petruzza (University of Utah – Salt Lake City, US) [dblp]
• Maria Riveiro (Univ. of Skövde, SE & Univ. of Jönköning, SE) [dblp]
• Carlos E. Scheidegger (University of Arizona – Tucson, US) [dblp]
• Sarah Schulz (Ada Health – Berlin, DE) [dblp]
• Hendrik Strobelt (MIT-IBM Watson AI Lab – Cambridge, US) [dblp]
• Simone Stumpf (City, University of London, GB) [dblp]
• Jayaraman Thiagarajan (LLNL – Livermore, US) [dblp]
• Jarke J. van Wijk (TU Eindhoven, NL) [dblp]

Im Falle von Fehlern oder Fragen bezüglich den Links zu dblp, kontaktieren Sie bitte Michael Wagner