Abstract
ACM/IEEE Workshop on Machine Learning for CAD (MLCAD) was held on September 2–4, 2020 in Canmore, AB, Canada. The location at the entrance to Banff National Park maintained a long tradition of mountain locations for technical meetings ( <xref ref-type="fig" rid="fig1" xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">Figure 1</xref> ). The workshop welcomed 52 participants including eight graduate students. The program committee was cochaired by Hussam Amrouch of Karlsruhe Institute of Technology and Bei Yu of Chinese University of Hong Kong. General Chairs were Marilyn Wolf and Jörg Henkel. The program included 30 contributed presentations based on submissions to the program committee as well as five invited talks. The program included talks from both industry and academia; participants were based in Asia, Europe, and North America. The program provided time for in-depth discussion; topics included appropriate types of ML methods for various types of CAD problems and challenges associated with training data.
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