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<rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>Revisiting Deep Learning Models for Tabular Data · HackerPapers discussions</title><link>https://hackerpaper.kaipfister.de/p/2106.11959/</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/2106.11959/feed.xml" rel="self" type="application/rss+xml" /><item><title>Revisiting Deep Learning Models for Tabular Data — mentioned by mountainriver</title><link>https://news.ycombinator.com/item?id=31481098</link><guid isPermaLink="false">urn:hackerpapers:mention:2106.11959:31481098</guid><pubDate>Mon, 23 May 2022 16:24:32 GMT</pubDate><description>&lt;p&gt;This https://arxiv.org/pdf/2106.11959.pdf would say differently. It shows there isn&amp;#x27;t a goto architecture when compared to modern DL&lt;/p&gt;&lt;p&gt;&lt;a href="https://hackerpaper.kaipfister.de/p/2106.11959/"&gt;Paper and discussion history&lt;/a&gt;. A mention is not an endorsement.&lt;/p&gt;</description><category>cs.LG</category></item><item><title>Revisiting Deep Learning Models for Tabular Data — mentioned by mountainriver</title><link>https://news.ycombinator.com/item?id=31481090</link><guid isPermaLink="false">urn:hackerpapers:mention:2106.11959:31481090</guid><pubDate>Mon, 23 May 2022 16:24:00 GMT</pubDate><description>&lt;p&gt;Not saying they should be the first tool of choice, saying that the study doesn&amp;#x27;t compare GB to more modern DL techniques like transformers. This is a good analysis https://arxiv.org/pdf/2106.11959.pdf and finds there isn&amp;#x27;t a go to architecture&lt;/p&gt;&lt;p&gt;&lt;a href="https://hackerpaper.kaipfister.de/p/2106.11959/"&gt;Paper and discussion history&lt;/a&gt;. A mention is not an endorsement.&lt;/p&gt;</description><category>cs.LG</category></item><item><title>Revisiting Deep Learning Models for Tabular Data — mentioned by vpj</title><link>https://news.ycombinator.com/item?id=27602389</link><guid isPermaLink="false">urn:hackerpapers:mention:2106.11959:27602389</guid><pubDate>Wed, 23 Jun 2021 09:05:08 GMT</pubDate><description>&lt;p&gt;PDF: https://arxiv.org/pdf/2106.11959v1.pdf&lt;/p&gt;&lt;p&gt;&lt;a href="https://hackerpaper.kaipfister.de/p/2106.11959/"&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>
