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<rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>Random-Bridges as Stochastic Transports for Generative Models · HackerPapers discussions</title><link>https://hackerpaper.kaipfister.de/p/2512.14190/</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/2512.14190/feed.xml" rel="self" type="application/rss+xml" /><item><title>Random-Bridges as Stochastic Transports for Generative Models — mentioned by sesenai</title><link>https://news.ycombinator.com/item?id=47313268</link><guid isPermaLink="false">urn:hackerpapers:mention:2512.14190:47313268</guid><pubDate>Mon, 09 Mar 2026 18:31:17 GMT</pubDate><description>&lt;p&gt;Co-author here. This paper proposes random bridges as an alternative transport mechanism for generative models. The core idea is that instead of using diffusion processes (which require many sampling steps and are computationally expensive), we use stochastic bridge processes to transport between distributions. The key results: Competitive FID scores with significantly fewer sampling steps compared to standard diffusion models The framework is flexible — it generalises several existing approaches including score-based diffusion and flow matching Reduced computational cost at inference time…&lt;/p&gt;&lt;p&gt;&lt;a href="https://hackerpaper.kaipfister.de/p/2512.14190/"&gt;Paper and discussion history&lt;/a&gt;. A mention is not an endorsement.&lt;/p&gt;</description><category>cs.LG</category></item><item><title>Random-Bridges as Stochastic Transports for Generative Models — HN submission</title><link>https://news.ycombinator.com/item?id=47313267</link><guid isPermaLink="false">urn:hackerpapers:submission:2512.14190:47313267</guid><pubDate>Mon, 09 Mar 2026 18:31:17 GMT</pubDate><description>&lt;p&gt;Random-Bridges as Stochastic Transports for Generative Models&lt;/p&gt;&lt;p&gt;&lt;/p&gt;&lt;p&gt;2 points; 1 discussion reply on HN. &lt;a href="https://hackerpaper.kaipfister.de/p/2512.14190/"&gt;Paper and source history&lt;/a&gt;. A submission is not an endorsement.&lt;/p&gt;</description><category>cs.LG</category></item></channel></rss>
