<?xml version="1.0" encoding="UTF-8"?>
<rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>Deep Learning: A Bayesian Perspective · HackerPapers discussions</title><link>https://hackerpaper.kaipfister.de/p/1706.00473/</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/1706.00473/feed.xml" rel="self" type="application/rss+xml" /><item><title>Deep Learning: A Bayesian Perspective — mentioned by Gtifn</title><link>https://news.ycombinator.com/item?id=14792914</link><guid isPermaLink="false">urn:hackerpapers:mention:1706.00473:14792914</guid><pubDate>Mon, 17 Jul 2017 22:49:04 GMT</pubDate><description>&lt;p&gt;What do you think about a bayesian interpretation of the above as MAP/MLE? https://arxiv.org/abs/1706.00473&lt;/p&gt;&lt;p&gt;&lt;a href="https://hackerpaper.kaipfister.de/p/1706.00473/"&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>
