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ICTR Enrichment Series: An Introduction to Generative Adversarial Networks with an Application to Denoising EEG

Authors
Oates, Tim
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Date
2019-12-10
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Peer Reviewed
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Poster/Presentation
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Clinical and Translational Research at UMB
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https://youtu.be/QbEiqRgDd_Q
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In this presentation, Dr. Tim Oates will introduce GAN architectures, describe how they are learned, and present a number of example applications, including generating "fake" people. Dr. Oates will also review some recent work done in his lab using GANs to denoise EEG data. Dr. Oates’ research focuses on artificial intelligence, machine learning, robotics, and natural language processing. He recently held a Post-doc position at the MIT Laboratory.
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denoising EEG
 generative adversarial networks (GAN)
 Electroencephalography
 Machine Learning
 Independent component analysis (ICA)
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http://hdl.handle.net/10713/13729
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