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<rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>DRAW: A Recurrent Neural Network For Image Generation · HackerPapers discussions</title><link>https://hackerpaper.kaipfister.de/p/1502.04623/</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/1502.04623/feed.xml" rel="self" type="application/rss+xml" /><item><title>DRAW: A Recurrent Neural Network For Image Generation — mentioned by 0-_-0</title><link>https://news.ycombinator.com/item?id=22374780</link><guid isPermaLink="false">urn:hackerpapers:mention:1502.04623:22374780</guid><pubDate>Thu, 20 Feb 2020 13:07:35 GMT</pubDate><description>&lt;p&gt;&amp;gt; But much more interesting to me is a lossless domain-specific compressor, which I’m not aware of any examples of. (Please tell me if about some if you know them!) A bit academic, but if you check out this paper from 2015 https://arxiv.org/pdf/1502.04623.pdf on a neural network trained on binarised MNIST (28x28 pixel images), Table 2 quotes entropy figures of 116.815 after converting to bits, which would be 28*28/116.815=6.71x compression (if used as a compressor)&lt;/p&gt;&lt;p&gt;&lt;a href="https://hackerpaper.kaipfister.de/p/1502.04623/"&gt;Paper and discussion history&lt;/a&gt;. A mention is not an endorsement.&lt;/p&gt;</description><category>cs.CV</category></item><item><title>DRAW: A Recurrent Neural Network For Image Generation — mentioned by nl</title><link>https://news.ycombinator.com/item?id=12610660</link><guid isPermaLink="false">urn:hackerpapers:mention:1502.04623:12610660</guid><pubDate>Fri, 30 Sep 2016 05:28:46 GMT</pubDate><description>&lt;p&gt;Expecting 2 years of research by around 20 of the best DNN researchers on the planet to be compressed into a StackOverflow answer before it has been done seems a fairly large amount to expect. Not a huge fan of the negativity on StackOverflow, but until August 2016 (when the paper this was based on was published - or maybe 2015, with DRAW[2]) people actively working in this area didn&amp;#x27;t think it was possible. Also, the single answer there certainly didn&amp;#x27;t say anything like it was a stupid idea. I don&amp;#x27;t think the author of that answer knew much about autoencoders. Also^2, your question isn&amp;#x27;t…&lt;/p&gt;&lt;p&gt;&lt;a href="https://hackerpaper.kaipfister.de/p/1502.04623/"&gt;Paper and discussion history&lt;/a&gt;. A mention is not an endorsement.&lt;/p&gt;</description><category>cs.CV</category></item><item><title>DRAW: A Recurrent Neural Network For Image Generation — mentioned by themann9</title><link>https://news.ycombinator.com/item?id=10180113</link><guid isPermaLink="false">urn:hackerpapers:mention:1502.04623:10180113</guid><pubDate>Mon, 07 Sep 2015 04:59:27 GMT</pubDate><description>&lt;p&gt;Guy, the only thing abundantly clear is that you are full of dung. Your shameless self-promotion may piss-off the police chief here - murbard2, so be more careful. Ten digits better classified, out of 10000? With a structure more complicated than a human DNA vs two lines of code? Congratulations! Or, and how are your &amp;quot;stairways-to-heaven&amp;quot; even remotely universal? Show us something these networks have generated like the VAE or Gibbs/ACE papers? Perhaps you can show some density estimation results as in http://arxiv.org/abs/1502.04623 or http://arxiv.org/abs/1508.06585? Oja and Hyvarinen are…&lt;/p&gt;&lt;p&gt;&lt;a href="https://hackerpaper.kaipfister.de/p/1502.04623/"&gt;Paper and discussion history&lt;/a&gt;. A mention is not an endorsement.&lt;/p&gt;</description><category>cs.CV</category></item><item><title>DRAW: A Recurrent Neural Network For Image Generation — HN submission</title><link>https://news.ycombinator.com/item?id=9125012</link><guid isPermaLink="false">urn:hackerpapers:submission:1502.04623:9125012</guid><pubDate>Sat, 28 Feb 2015 20:53:39 GMT</pubDate><description>&lt;p&gt;DRAW: A Recurrent Neural Network for Image Generation [pdf]&lt;/p&gt;&lt;p&gt;&lt;/p&gt;&lt;p&gt;2 points; 0 discussion replies on HN. &lt;a href="https://hackerpaper.kaipfister.de/p/1502.04623/"&gt;Paper and source history&lt;/a&gt;. A submission is not an endorsement.&lt;/p&gt;</description><category>cs.CV</category></item><item><title>DRAW: A Recurrent Neural Network For Image Generation — HN submission</title><link>https://news.ycombinator.com/item?id=9062635</link><guid isPermaLink="false">urn:hackerpapers:submission:1502.04623:9062635</guid><pubDate>Tue, 17 Feb 2015 15:17:02 GMT</pubDate><description>&lt;p&gt;DRAW: A Recurrent Neural Network For Image Generation [pdf]&lt;/p&gt;&lt;p&gt;&lt;/p&gt;&lt;p&gt;26 points; 7 discussion replies on HN. &lt;a href="https://hackerpaper.kaipfister.de/p/1502.04623/"&gt;Paper and source history&lt;/a&gt;. A submission is not an endorsement.&lt;/p&gt;</description><category>cs.CV</category></item></channel></rss>
