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<rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>Learning high-dimensional probability distributions using tree tensor networks · HackerPapers discussions</title><link>https://hackerpaper.kaipfister.de/p/1912.07913/</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/1912.07913/feed.xml" rel="self" type="application/rss+xml" /><item><title>Learning high-dimensional probability distributions using tree tensor networks — mentioned by nickpsecurity</title><link>https://news.ycombinator.com/item?id=36905820</link><guid isPermaLink="false">urn:hackerpapers:mention:1912.07913:36905820</guid><pubDate>Fri, 28 Jul 2023 12:23:47 GMT</pubDate><description>&lt;p&gt;I&amp;#x27;ve never seen anything about training on probability distributions or trees of them. Do you have articles with examples you could share with us? I did try a quick search for it. Found some interesting papers. The links to them are below in case anyone finds them interesting. https://arxiv.org/abs/2212.11481 https://towardsdatascience.com/a-new-way-to-predict-probabil... https://arxiv.org/pdf/1912.07913.pdf https://dukespace.lib.duke.edu/dspace/bitstream/handle/10161...&lt;/p&gt;&lt;p&gt;&lt;a href="https://hackerpaper.kaipfister.de/p/1912.07913/"&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>
