<?xml version="1.0" encoding="utf-8" standalone="yes"?><rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom" xmlns:content="http://purl.org/rss/1.0/modules/content/"><channel><title>GNN on WishBottle</title><link>/tags/gnn/</link><description>Recent content in GNN on WishBottle</description><generator>Hugo -- 0.156.0</generator><language>zh-cn</language><lastBuildDate>Mon, 06 Apr 2026 00:00:00 +0000</lastBuildDate><atom:link href="/tags/gnn/index.xml" rel="self" type="application/rss+xml"/><item><title>图神经网络（GNN）入门｜文章笔记与要点整理</title><link>/posts/gnn%E5%85%A5%E9%97%A8/</link><pubDate>Mon, 06 Apr 2026 00:00:00 +0000</pubDate><guid>/posts/gnn%E5%85%A5%E9%97%A8/</guid><description>&lt;blockquote&gt;
&lt;p&gt;此笔记是在阅读&lt;code&gt;&amp;lt;&amp;lt;A Gentle Introduction to Graph Neural Networks&amp;gt;&amp;gt;&lt;/code&gt;的过程中写下的&lt;br&gt;
阅读文章的同时观看了B站UP主 &lt;code&gt;跟李沐学AI&lt;/code&gt; 的视频 &lt;code&gt;零基础多图详解图神经网络（GNN/GCN）【论文精读】&lt;/code&gt;&lt;br&gt;
文章链接 :&lt;a href="https://distill.pub/2021/gnn-intro/"&gt;A Gentle Introduction to Graph Neural Networks&lt;/a&gt;&lt;br&gt;
视频链接 :&lt;a href="https://www.bilibili.com/video/BV1iT4y1d7zP?buvid=XY5DC4D50EA9C9301D3F3D7ABA9CAD232145D&amp;amp;from_spmid=search.search-result.0.0&amp;amp;is_story_h5=false&amp;amp;mid=eXA%2F5vaSVq4mtRJm4lYcrQ%3D%3D&amp;amp;plat_id=114&amp;amp;share_from=ugc&amp;amp;share_medium=android&amp;amp;share_plat=android&amp;amp;share_session_id=e37da1a8-de1f-4054-84aa-5ce2b20812a2&amp;amp;share_source=COPY&amp;amp;share_tag=s_i&amp;amp;spmid=united.player-video-detail.0.0&amp;amp;timestamp=1774769540&amp;amp;unique_k=C5u0727&amp;amp;up_id=1567748478&amp;amp;vd_source=b7fe282ae22dcad10ba845b5eea36a47"&gt;零基础多图详解图神经网络（GNN/GCN）【论文精读】_哔哩哔哩_bilibili&lt;/a&gt;&lt;/p&gt;
&lt;/blockquote&gt;
&lt;h1 id="0-标题解读"&gt;0. 标题解读&lt;/h1&gt;
&lt;h2 id="01-主标题"&gt;0.1 主标题&lt;/h2&gt;
&lt;p&gt;&lt;code&gt;A Gentle Introduction to Graph Neural Networks&lt;/code&gt;&lt;br&gt;
直接说明本文是关于 &lt;strong&gt;图神经网络(GNN)&lt;/strong&gt; 的简单的介绍&lt;/p&gt;
&lt;h2 id="02-副标题"&gt;0.2 副标题&lt;/h2&gt;
&lt;p&gt;&lt;code&gt;Neural networks have been adapted to leverage the structure and properties of graphs. We explore the components needed for building a graph neural network - and motivate the design choices behind them.&lt;/code&gt;&lt;br&gt;
讲的是 : 图神经网络 被用在处理图的结构和特效上, 这篇文章来探索构建图神经网络需要哪些模块, 以及这背后的思想是什么&lt;/p&gt;</description></item></channel></rss>