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VERSION:2.0
PRODID:EuroVis 2021
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DTSTART:19700329T020000
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BEGIN:VEVENT
DTSTAMP:20210614T073009Z
UID:20210616T110000Z@sp-1.eurovis.org
DTSTART;TZID=Europe/Berlin:20210616T110000
DTEND;TZID=Europe/Berlin:20210616T124000
SUMMARY:sp-1: Machine Learning & SciVis Applications
DESCRIPTION:Loss-contribution-based in situ visualization for neural network training\nTeng-Yok Lee\n\nVATUN: Visual Analytics for Testing and Understanding Convolutional Neural Networks\nCheonbok Park, Soyoung Yang, Inyoup Na, Sunghyo Chung, Sungbok Shin, Bum Chul Kwon, Deokgun Park, Jaegul Choo\n\nRoomCanvas: A Visualization Technique for Spatiotemporal Temperature Data in Smart Homes\nBastian König, Daniel Limberger, Jan Klimke, Benjamin Hagedorn, Jürgen Döllner\n\nSailVis: Reconstruction and multifaceted visualization of sail shape\nDanfeng Mu, Marcos Pieras, Douwe Broekens, Ricardo Marroquim\n\nRISSAD: Rule-based Interactive Semi-Supervised Anomaly Detection\nJiahao Deng, Eli T Brown
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