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<rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>A Dynamic Programming Algorithm for Inference in Recursive Probabilistic Programs · HackerPapers discussions</title><link>https://hackerpaper.kaipfister.de/p/1206.3555/</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/1206.3555/feed.xml" rel="self" type="application/rss+xml" /><item><title>A Dynamic Programming Algorithm for Inference in Recursive Probabilistic Programs — mentioned by cf</title><link>https://news.ycombinator.com/item?id=12421917</link><guid isPermaLink="false">urn:hackerpapers:mention:1206.3555:12421917</guid><pubDate>Sun, 04 Sep 2016 00:10:55 GMT</pubDate><description>&lt;p&gt;So there has been work done in compiling probabilistic programs directly into C or C++ [1]. Your intuition is correct that in many of these languages if you wrote an HMM and did MAP inference over it you wouldn&amp;#x27;t recover the Viterbi algorithm, but there is some code in WebPPL[2] that handles this case as outlined in https://arxiv.org/abs/1206.3555. [1] https://web.stanford.edu/~ngoodman/papers/aistats2014-shred.... [2] http://docs.webppl.org/en/master/inference/methods.html#enum...&lt;/p&gt;&lt;p&gt;&lt;a href="https://hackerpaper.kaipfister.de/p/1206.3555/"&gt;Paper and discussion history&lt;/a&gt;. A mention is not an endorsement.&lt;/p&gt;</description><category>cs.AI</category></item></channel></rss>
