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<rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>Light Microscopy at Maximal Precision · HackerPapers discussions</title><link>https://hackerpaper.kaipfister.de/p/1702.07336/</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/1702.07336/feed.xml" rel="self" type="application/rss+xml" /><item><title>Light Microscopy at Maximal Precision — mentioned by peppery</title><link>https://news.ycombinator.com/item?id=15841371</link><guid isPermaLink="false">urn:hackerpapers:mention:1702.07336:15841371</guid><pubDate>Mon, 04 Dec 2017 04:03:01 GMT</pubDate><description>&lt;p&gt;Your work with ML and images sounds incredible! Do you have a link (e.g. on arxiv or elsewhere) that describes your approach using ML for image reconstruction in greater detail? How would you recommend building up one&amp;#x27;s combined intuition in optical theory, the relevant ML techniques, and the biological substances themselves, to the level where you can innovate in this task as you have done? Also, for those interested in the concept of building better images using higher fidelity simulations of the microscope itself, presumably Andrew meant studies along these lines…&lt;/p&gt;&lt;p&gt;&lt;a href="https://hackerpaper.kaipfister.de/p/1702.07336/"&gt;Paper and discussion history&lt;/a&gt;. A mention is not an endorsement.&lt;/p&gt;</description><category>cond-mat.soft</category></item></channel></rss>
