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<rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>Practical Deep Learning with Bayesian Principles · HackerPapers discussions</title><link>https://hackerpaper.kaipfister.de/p/1906.02506/</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/1906.02506/feed.xml" rel="self" type="application/rss+xml" /><item><title>Practical Deep Learning with Bayesian Principles — mentioned by benrbray</title><link>https://news.ycombinator.com/item?id=22026751</link><guid isPermaLink="false">urn:hackerpapers:mention:1906.02506:22026751</guid><pubDate>Sun, 12 Jan 2020 15:45:30 GMT</pubDate><description>&lt;p&gt;I interned for a team working in this area, and my supervisor was quite happy with their results using Bayesian Deep Learning on ImageNet: https://arxiv.org/abs/1906.02506&lt;/p&gt;&lt;p&gt;&lt;a href="https://hackerpaper.kaipfister.de/p/1906.02506/"&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>
