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<rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>Training deep neural networks for the inverse design of nanophotonic structures · HackerPapers discussions</title><link>https://hackerpaper.kaipfister.de/p/1710.04724/</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/1710.04724/feed.xml" rel="self" type="application/rss+xml" /><item><title>Training deep neural networks for the inverse design of nanophotonic structures — mentioned by LolWolf</title><link>https://news.ycombinator.com/item?id=25129992</link><guid isPermaLink="false">urn:hackerpapers:mention:1710.04724:25129992</guid><pubDate>Tue, 17 Nov 2020 21:19:29 GMT</pubDate><description>&lt;p&gt;Thanks! This is a good question; AI and DL has been used for a little bit in physical design (in a scalable way starting roughly the past few years or so). The paper has some references at the top of page 26), but [0] and [1] have decent overviews as well! ----- [0] https://www.degruyter.com/view/journals/nanoph/9/5/article-p... [1] https://pubs.acs.org/doi/10.1021/acsphotonics.7b01377 (an arXiv link is found here: https://arxiv.org/pdf/1710.04724.pdf)&lt;/p&gt;&lt;p&gt;&lt;a href="https://hackerpaper.kaipfister.de/p/1710.04724/"&gt;Paper and discussion history&lt;/a&gt;. A mention is not an endorsement.&lt;/p&gt;</description><category>physics.optics</category></item></channel></rss>
