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<rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>Causal Theories: A Categorical Perspective on Bayesian Networks · HackerPapers discussions</title><link>https://hackerpaper.kaipfister.de/p/1301.6201/</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/1301.6201/feed.xml" rel="self" type="application/rss+xml" /><item><title>Causal Theories: A Categorical Perspective on Bayesian Networks — mentioned by thraway180306</title><link>https://news.ycombinator.com/item?id=16680934</link><guid isPermaLink="false">urn:hackerpapers:mention:1301.6201:16680934</guid><pubDate>Mon, 26 Mar 2018 17:53:24 GMT</pubDate><description>&lt;p&gt;About ML-related research, Fong also piqued my interest earlier with his categorification of almost PGMs. Though it didn&amp;#x27;t inspire him or anyone to bring effective methods of algebra to PGM and improve the base theory, making the exercise really shine. So like with many categorification research it&amp;#x27;s just a 72-page statement „it can be done”. Brendan Fong (2012) Causal Theories: A Categorical Perspective on Bayesian Networks https://arxiv.org/abs/1301.6201&lt;/p&gt;&lt;p&gt;&lt;a href="https://hackerpaper.kaipfister.de/p/1301.6201/"&gt;Paper and discussion history&lt;/a&gt;. A mention is not an endorsement.&lt;/p&gt;</description><category>math.PR</category></item></channel></rss>
