<?xml version="1.0" encoding="utf-8" standalone="yes"?><rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>Geometric Deep Learning on English AI Terms Dictionary</title><link>https://terms-en.ai-term-hub.com/en/tags/geometric-deep-learning/</link><description>Recent content in Geometric Deep Learning on English AI Terms Dictionary</description><generator>Hugo</generator><language>en-us</language><lastBuildDate>Sat, 18 Jul 2026 11:44:44 +0000</lastBuildDate><atom:link href="https://terms-en.ai-term-hub.com/en/tags/geometric-deep-learning/index.xml" rel="self" type="application/rss+xml"/><item><title>Group</title><link>https://terms-en.ai-term-hub.com/en/terms/group/</link><pubDate>Sat, 18 Jul 2026 09:33:06 +0000</pubDate><guid>https://terms-en.ai-term-hub.com/en/terms/group/</guid><description>&lt;h2 id="definition">Definition&lt;/h2>
&lt;p>In mathematics and theoretical computer science, a group is a set G together with a binary operation that satisfies four axioms: closure, associativity, identity, and invertibility. In AI, group theory is increasingly applied in geometric deep learning to ensure models respect symmetries and invariances in data, such as rotational symmetry in images. By designing neural networks that operate on group structures, researchers can create more efficient and robust models that generalize better across different orientations or transformations of input data.&lt;/p></description></item></channel></rss>