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<?xml-stylesheet type="text/xsl" href="../assets/xml/rss.xsl" media="all"?><rss version="2.0" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>Asymptotic Labs (Posts about neural networks, network architecture, convolutions)</title><link>http://asymptoticlabs.com/</link><description></description><atom:link href="http://asymptoticlabs.com/categories/cat_neural-networks-network-architecture-convolutions.xml" rel="self" type="application/rss+xml"></atom:link><language>en</language><copyright>Contents © 2022 &lt;a href="mailto:quidditymaster@gmail.com"&gt;Tim Anderton&lt;/a&gt; </copyright><lastBuildDate>Wed, 31 Aug 2022 21:28:34 GMT</lastBuildDate><generator>Nikola (getnikola.com)</generator><docs>http://blogs.law.harvard.edu/tech/rss</docs><item><title>Permutation CNN</title><link>http://asymptoticlabs.com/posts/permutation-cnn.html</link><dc:creator>Tim Anderton</dc:creator><description>&lt;div class="cell border-box-sizing text_cell rendered"&gt;&lt;div class="prompt input_prompt"&gt;
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&lt;p&gt;To kick off &lt;a href="http://asymptoticlabs.com/posts/blogging-blitz-2019.html"&gt; the blitz &lt;/a&gt; I'm going to begin with an idea I had back in April of this year which I think could be a lot of fun to play with but which I don't feel like I have had enough time to get a real feel for. The idea is in essence "why not replace all the dense layers in a neural network with convolutional layers?".&lt;/p&gt;
&lt;p&gt;&lt;a href="http://asymptoticlabs.com/posts/permutation-cnn.html"&gt;Read more…&lt;/a&gt; (13 min remaining to read)&lt;/p&gt;&lt;/div&gt;&lt;/div&gt;&lt;/div&gt;&lt;/body&gt;&lt;/html&gt;
</description><guid>http://asymptoticlabs.com/posts/permutation-cnn.html</guid><pubDate>Sun, 22 Dec 2019 07:00:00 GMT</pubDate></item></channel></rss>