VIS Full Papers: Explainable AI and Machine Learning
Session chair: Hendrik Strobelt
Live-stream room: Bourbon
2021-10-27T13:00:00Z – 2021-10-27T14:30:00ZGMT-0600Change your timezone on the schedule page
2021-10-27T13:00:00Z – 2021-10-27T14:30:00Z
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AffectiveTDA: Using Topological Data Analysis to Improve Analysis and Explainability in Affective Computing
Hamza Elhamdadi
recorded 2021-10-27T13:00:00Z – 2021-10-27T13:15:00ZGMT-0600Change your timezone on the schedule page
Human-in-the-loop Extraction of Interpretable Concepts in Deep Learning Models
Zhenge Zhao
recorded 2021-10-27T13:15:00Z – 2021-10-27T13:30:00ZGMT-0600Change your timezone on the schedule page
Towards Visual Explainable Active Learning for Zero-Shot Classification
Shichao Jia
recorded 2021-10-27T13:30:00Z – 2021-10-27T13:45:00ZGMT-0600Change your timezone on the schedule page
M^2Lens: Visualizing and Explaining Multimodal Models for Sentiment Analysis
Xingbo Wang
recorded 2021-10-27T13:45:00Z – 2021-10-27T14:00:00ZGMT-0600Change your timezone on the schedule page
NeuroCartography: Scalable Automatic Visual Summarization of Concepts in Deep Neural Networks
Haekyu Park
recorded 2021-10-27T14:00:00Z – 2021-10-27T14:15:00ZGMT-0600Change your timezone on the schedule page
Visual Analytics for RNN-Based Deep Reinforcement Learning
Junpeng Wang
recorded 2021-10-27T14:15:00Z – 2021-10-27T14:30:00ZGMT-0600Change your timezone on the schedule page
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