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<p><b><font size="5">Entropy-Aware Graph Neural,Networks: Theory,
Methods,,and Applications</font></b> - </p>
<p>Special Issue in MDPI Entropy</p>
<p>For submission information, please visit the SI webpage:</p>
<p><a class="moz-txt-link-freetext" href="https://www.mdpi.com/journal/entropy/special_issues/1028YT5CB9">https://www.mdpi.com/journal/entropy/special_issues/1028YT5CB9</a></p>
<p>Submission deadline: June 30, 2026</p>
<p>Guest Editors: Junran Wu, Nan Wang, Friedhelm Schwenker</p>
<p>Graph neural networks (GNNs) have emerged as a fundamental
framework for learning from graph-structured data, demonstrating
remarkable success across domains such as social network analysis,
recommender systems, bioinformatics, and financial modeling.
Entropy and information-theoretic principles provide a natural
lens for analyzing the expressivity, generalization, and
robustness of GNNs. From the viewpoint of Fisher information,
mutual information, and information bottlenecks, entropy-aware
frameworks can help explain and improve the propagation,
compression, and preservation of structural information in
networks.<br>
</p>
<p>This Special Issue aims to advance the understanding of
entropy-aware graph neural networks by bridging<br>
information theory and graph representation learning. We invite
original research and review articles that<br>
- provide information-theoretic analysis of GNN mechanisms and
architectures,<br>
- propose new entropy- or information-driven GNN methods, or<br>
- explore applications of entropy-aware graph learning<br>
in scientific, industrial, and social domains.</p>
<p><br>
</p>
<pre class="moz-signature" cols="72">--
Prof. Dr. Friedhelm Schwenker
University of Ulm
Institute of Neural Information Processing
D-89069 Ulm, Germany
phone: +49-731-50-24159
fax: +49-731-50-24156
email: <a class="moz-txt-link-abbreviated" href="mailto:friedhelm.schwenker@uni-ulm.de">friedhelm.schwenker@uni-ulm.de</a>
www: <a class="moz-txt-link-freetext" href="https://www.uni-ulm.de/in/neuroinformatik/institut/hidden/f-schwenker/">https://www.uni-ulm.de/in/neuroinformatik/institut/hidden/f-schwenker/</a></pre>
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