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	<title>Symbolic regression &#8211; BIOENGINEER.ORG</title>
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		<title>Revolutionary Neural Symbolic Model Transforms Space Physics</title>
		<link>https://bioengineer.org/revolutionary-neural-symbolic-model-transforms-space-physics/</link>
		
		<dc:creator><![CDATA[Bioengineer]]></dc:creator>
		<pubDate>Wed, 15 Oct 2025 12:17:37 +0000</pubDate>
				<category><![CDATA[Technology]]></category>
		<category><![CDATA[Artificial intelligence in physics]]></category>
		<category><![CDATA[Neural symbolic models]]></category>
		<category><![CDATA[PhyE2E framework]]></category>
		<category><![CDATA[Space physics research]]></category>
		<category><![CDATA[Symbolic regression]]></category>
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					<description><![CDATA[In a groundbreaking endeavor to harness artificial intelligence for the understanding of complex physical systems, researchers have introduced an innovative framework named PhyE2E. This neural-symbolic model aims to address persistent challenges in the field of symbolic regression, particularly the issues of scalability and interpretability when uncovering essential physics formulas from observational data. Symbolic regression is [&#8230;]]]></description>
		
		
		
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