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<rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>EEG-GAN: Generative adversarial networks for electroencephalograhic (EEG) brain signals · HackerPapers discussions</title><link>https://hackerpaper.kaipfister.de/p/1806.01875/</link><description>Collected HN comments and submissions linking this paper.</description><language>en</language><lastBuildDate>Mon, 02 Nov 2026 11:16:22 GMT</lastBuildDate><atom:link href="https://hackerpaper.kaipfister.de/p/1806.01875/feed.xml" rel="self" type="application/rss+xml" /><item><title>EEG-GAN: Generative adversarial networks for electroencephalograhic (EEG) brain signals — mentioned by TomMarius</title><link>https://news.ycombinator.com/item?id=19862401</link><guid isPermaLink="false">urn:hackerpapers:mention:1806.01875:19862401</guid><pubDate>Wed, 08 May 2019 20:09:11 GMT</pubDate><description>&lt;p&gt;Why are you condescending me? I studied applications of GAN nets for dozens of hours (still an amateur beginner of course). I didn&amp;#x27;t even know it was such a buzzword when I got started as I don&amp;#x27;t follow twitter etc. Here is a paper that talks about exactly what I am proposing, using GANs, minus evolved antennas: https://arxiv.org/abs/1806.01875 (it is no secret that this paper has inspired me to write this question - my thoughts were about improving it with evolved antennas). About the clean data requirement, it is common practice to record as much as possible once doctors open somebody&amp;#x27;s…&lt;/p&gt;&lt;p&gt;&lt;a href="https://hackerpaper.kaipfister.de/p/1806.01875/"&gt;Paper and discussion history&lt;/a&gt;. A mention is not an endorsement.&lt;/p&gt;</description><category>eess.SP</category></item></channel></rss>
