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<rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>Mind the Gap: A Study in Global Development through Persistent Homology · HackerPapers discussions</title><link>https://hackerpaper.kaipfister.de/p/1702.08593/</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/1702.08593/feed.xml" rel="self" type="application/rss+xml" /><item><title>Mind the Gap: A Study in Global Development through Persistent Homology — mentioned by kaitai</title><link>https://news.ycombinator.com/item?id=20143243</link><guid isPermaLink="false">urn:hackerpapers:mention:1702.08593:20143243</guid><pubDate>Mon, 10 Jun 2019 01:53:41 GMT</pubDate><description>&lt;p&gt;There are a number of approaches; since it&amp;#x27;s still relatively new, there&amp;#x27;s a lot of &amp;quot;playing around&amp;quot; with techniques. 1) The first idea is to just see which topological features persist as the filtration/threshold parameter varies. I personally find the barcode illustration, rather than the birth-death diagram, to be more intuitive in this respect. For instance, say you had LIDAR data about a vehicle. Looking at the persistent homology of this point cloud could allow you to ascertain the size and number of windows (smaller windows would have shorter persistence than larger windows, and the…&lt;/p&gt;&lt;p&gt;&lt;a href="https://hackerpaper.kaipfister.de/p/1702.08593/"&gt;Paper and discussion history&lt;/a&gt;. A mention is not an endorsement.&lt;/p&gt;</description><category>math.AT</category></item></channel></rss>
