<?xml version="1.0" encoding="UTF-8"?><rss version="2.0"
	xmlns:content="http://purl.org/rss/1.0/modules/content/"
	xmlns:wfw="http://wellformedweb.org/CommentAPI/"
	xmlns:dc="http://purl.org/dc/elements/1.1/"
	xmlns:atom="http://www.w3.org/2005/Atom"
	xmlns:sy="http://purl.org/rss/1.0/modules/syndication/"
	xmlns:slash="http://purl.org/rss/1.0/modules/slash/"
	>

<channel>
	<title>receptive fields &#8211; BIOENGINEER.ORG</title>
	<atom:link href="https://bioengineer.org/tag/receptive-fields/feed/" rel="self" type="application/rss+xml" />
	<link>https://bioengineer.org</link>
	<description>Bioengineering</description>
	<lastBuildDate>Sat, 17 Oct 2026 12:22:09 +0000</lastBuildDate>
	<language>en-US</language>
	<sy:updatePeriod>
	hourly	</sy:updatePeriod>
	<sy:updateFrequency>
	1	</sy:updateFrequency>
	<generator>https://wordpress.org/?v=7.1.3</generator>

<image>
	<url>https://bioengineer.org/wp-content/uploads/2019/09/cropped-bioengineering-32x32.png</url>
	<title>receptive fields &#8211; BIOENGINEER.ORG</title>
	<link>https://bioengineer.org</link>
	<width>32</width>
	<height>32</height>
</image> 
<site xmlns="com-wordpress:feed-additions:1">72741379</site>	<item>
		<title>When Neural Networks Learn Like Brains: Locality Beats Weight Sharing in Hebbian Vision Models</title>
		<link>https://bioengineer.org/when-neural-networks-learn-like-brains-locality-beats-weight-sharing-in-hebbian-vision-models/</link>
		
		<dc:creator><![CDATA[]]></dc:creator>
		<pubDate>Sat, 17 Oct 2026 12:22:09 +0000</pubDate>
				<category><![CDATA[Health]]></category>
		<category><![CDATA[Technology]]></category>
		<category><![CDATA[biological constraints]]></category>
		<category><![CDATA[CIFAR-10]]></category>
		<category><![CDATA[Computational neuroscience]]></category>
		<category><![CDATA[convolutional neural networks]]></category>
		<category><![CDATA[Hebbian learning]]></category>
		<category><![CDATA[local plasticity]]></category>
		<category><![CDATA[neural computation]]></category>
		<category><![CDATA[principal component analysis]]></category>
		<category><![CDATA[receptive fields]]></category>
		<category><![CDATA[unsupervised learning]]></category>
		<category><![CDATA[visual representation learning]]></category>
		<category><![CDATA[weight sharing]]></category>
		<guid isPermaLink="false">https://bioengineer.org/?p=426923</guid>

					<description><![CDATA[A new computational neuroscience study shows that biologically constrained Hebbian learning can build useful visual representations without exact weight sharing, while revealing how deeply convolutional benchmarks depend on their surrounding architecture and protocol.]]></description>
		
		
		
		<post-id xmlns="com-wordpress:feed-additions:1">426923</post-id>	</item>
	</channel>
</rss>
