<?xml version="1.0" encoding="UTF-8"?>
<rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>Modeling Industrial ADMET Data with Multitask Networks · HackerPapers discussions</title><link>https://hackerpaper.kaipfister.de/p/1606.08793/</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/1606.08793/feed.xml" rel="self" type="application/rss+xml" /><item><title>Modeling Industrial ADMET Data with Multitask Networks — mentioned by momeara</title><link>https://news.ycombinator.com/item?id=12787776</link><guid isPermaLink="false">urn:hackerpapers:mention:1606.08793:12787776</guid><pubDate>Tue, 25 Oct 2016 13:32:20 GMT</pubDate><description>&lt;p&gt;Several people have asked for background material for the workshop-- (Wallach, 2015, http://arxiv.org/pdf/1510.02855.pdf) AtomNet: A Deep Convolutional Neural Network for Bioactivity Prediction in Structure-based Drug Discovery (Duvenaud, 2015, http://papers.nips.cc/paper/5954-convolutional-networks-on-g...) Convolutional Networks on Graphs for Learning Molecular Fingerprints (Kearnes, 2016, http://arxiv.org/abs/1606.08793v1) Modeling Industrial ADMET Data with Multitask Networks (Gómez-Bombarelli, 2016, doi:10.1038/nmat4717) Design of efficient molecular organic light-emitting diodes by a…&lt;/p&gt;&lt;p&gt;&lt;a href="https://hackerpaper.kaipfister.de/p/1606.08793/"&gt;Paper and discussion history&lt;/a&gt;. A mention is not an endorsement.&lt;/p&gt;</description><category>stat.ML</category></item></channel></rss>
