<?xml version="1.0" encoding="utf-8" standalone="yes"?><rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>Energy-Minimisation on Aayush Bajaj's Augmenting Infrastructure</title><link>https://abaj.ai/tags/energy-minimisation/</link><description>Recent content in Energy-Minimisation on Aayush Bajaj's Augmenting Infrastructure</description><generator>Hugo</generator><language>en</language><copyright>© 2026 Aayush Bajaj</copyright><lastBuildDate>Mon, 31 Aug 2026 00:29:54 +1000</lastBuildDate><atom:link href="https://abaj.ai/tags/energy-minimisation/index.xml" rel="self" type="application/rss+xml"/><item><title>Markov Networks</title><link>https://abaj.ai/wiki/ml/pgm/markov-networks/</link><pubDate>Mon, 31 Aug 2026 00:29:54 +1000</pubDate><guid>https://abaj.ai/wiki/ml/pgm/markov-networks/</guid><description>&lt;p>some dependencies have no natural direction. two neighbouring pixels tend to share a label; two friends tend to vote alike; two adjacent atoms couple their spins. forcing an arrow onto these symmetric interactions — as a &lt;a
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>bayesian network&lt;/a> must — misrepresents them. the &lt;strong>markov network&lt;/strong> (markov random field, mrf) is the undirected alternative, born in statistical physics: edges express mutual compatibility, parametrised not by conditional probabilities but by unnormalised &lt;em>potentials&lt;/em>, with a global normalising constant picking up the bill.&lt;span class="margin-note" data-note="the trade is exactly that: local, symmetric, easy-to-change factors — in exchange for a partition function that is np-hard to evaluate">
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