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<rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>Detecting Spacecraft Anomalies Using LSTMs and Nonparametric Dynamic Thresholding · HackerPapers discussions</title><link>https://hackerpaper.kaipfister.de/p/1802.04431/</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/1802.04431/feed.xml" rel="self" type="application/rss+xml" /><item><title>Detecting Spacecraft Anomalies Using LSTMs and Nonparametric Dynamic Thresholding — mentioned by theonewolf</title><link>https://news.ycombinator.com/item?id=24969832</link><guid isPermaLink="false">urn:hackerpapers:mention:1802.04431:24969832</guid><pubDate>Mon, 02 Nov 2020 16:29:06 GMT</pubDate><description>&lt;p&gt;Not sure if this is close to the problems you want to study, but NASA applied Deep learning to anomaly detection on spacecraft telemetry and has some early results here: https://arxiv.org/pdf/1802.04431.pdf I&amp;#x27;m very interested in anomaly detection problems, so if you find anything good out there do comment back in!&lt;/p&gt;&lt;p&gt;&lt;a href="https://hackerpaper.kaipfister.de/p/1802.04431/"&gt;Paper and discussion history&lt;/a&gt;. A mention is not an endorsement.&lt;/p&gt;</description><category>cs.LG</category></item></channel></rss>
