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<rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>A Frequentist Statistical Introduction to Variational Inference, Autoencoders, and Diffusion Models · HackerPapers discussions</title><link>https://hackerpaper.kaipfister.de/p/2510.18777/</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/2510.18777/feed.xml" rel="self" type="application/rss+xml" /><item><title>A Frequentist Statistical Introduction to Variational Inference, Autoencoders, and Diffusion Models — mentioned by jmalicki</title><link>https://news.ycombinator.com/item?id=47474186</link><guid isPermaLink="false">urn:hackerpapers:mention:2510.18777:47474186</guid><pubDate>Sun, 22 Mar 2026 03:27:58 GMT</pubDate><description>&lt;p&gt;They do! https://arxiv.org/pdf/2510.18777 But that doesn&amp;#x27;t mean a frequentist views a VAE as a generative model! Putting it another way, Gaussian processes originated as a frequentist technique! But to a frequentist they are not generative.&lt;/p&gt;&lt;p&gt;&lt;a href="https://hackerpaper.kaipfister.de/p/2510.18777/"&gt;Paper and discussion history&lt;/a&gt;. A mention is not an endorsement.&lt;/p&gt;</description><category>stat.ML</category></item></channel></rss>
