Thumbnail Image
Item

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

Oates, Tim
Author
Oates, Tim
Advisor
Date
2019-12-10
Embargo until
Language
Book title
Journal
Publisher
Peer Reviewed
Type
Poster/Presentation
Video
Research Area
Jurisdiction
Collections
Clinical and Translational Research at UMB
Show all metadata
Files
Thumbnail Image
Promotional Flyer
Adobe PDF, 505.47 KB
Other Titles
See at
https://youtu.be/QbEiqRgDd_Q
Abstract
Data Availibility
Data / Code Location
Table of Contents
Description
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.
Series/Report No.
Sponsors
Rights/Terms
Citation
Keyword
denoising EEG
 generative adversarial networks (GAN)
 Electroencephalography
 Machine Learning
 Independent component analysis (ICA)
Identifier to cite or link to this item
http://hdl.handle.net/10713/13729
Scopus Identifier
Embedded videos