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<rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>BP-STDP: Approximating Backpropagation using Spike Timing Dependent Plasticity · HackerPapers discussions</title><link>https://hackerpaper.kaipfister.de/p/1711.04214/</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/1711.04214/feed.xml" rel="self" type="application/rss+xml" /><item><title>BP-STDP: Approximating Backpropagation using Spike Timing Dependent Plasticity — mentioned by 0lmer</title><link>https://news.ycombinator.com/item?id=26704203</link><guid isPermaLink="false">urn:hackerpapers:mention:1711.04214:26704203</guid><pubDate>Mon, 05 Apr 2021 20:25:22 GMT</pubDate><description>&lt;p&gt;But does predictive coding perceived as a valid theory for cortical neurons functioning? There was a paper from 2017 drawing similar conclusions about backprop approximation with Spike-Timing-Dependent Plasticity: https://arxiv.org/abs/1711.04214 Looks more grounded to current models of neuronal functioning. Nevertheless, it changed nothing in the field of deep learning since then.&lt;/p&gt;&lt;p&gt;&lt;a href="https://hackerpaper.kaipfister.de/p/1711.04214/"&gt;Paper and discussion history&lt;/a&gt;. A mention is not an endorsement.&lt;/p&gt;</description><category>cs.NE</category></item></channel></rss>
