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<oembed><version>1.0</version><provider_name>Microsoft Research</provider_name><provider_url>https://www.microsoft.com/en-us/research</provider_url><author_name>John Winn</author_name><author_url>https://www.microsoft.com/en-us/research/people/jwinn/</author_url><title>Belief Propagation with Strings - Microsoft Research</title><type>rich</type><width>600</width><height>338</height><html>&lt;blockquote class="wp-embedded-content" data-secret="syCkoh45TP"&gt;&lt;a href="https://www.microsoft.com/en-us/research/publication/belief-propagation-strings/"&gt;Belief Propagation with Strings&lt;/a&gt;&lt;/blockquote&gt;&lt;iframe sandbox="allow-scripts" security="restricted" src="https://www.microsoft.com/en-us/research/publication/belief-propagation-strings/embed/#?secret=syCkoh45TP" width="600" height="338" title="&#x201C;Belief Propagation with Strings&#x201D; &#x2014; Microsoft Research" data-secret="syCkoh45TP" frameborder="0" marginwidth="0" marginheight="0" scrolling="no" class="wp-embedded-content"&gt;&lt;/iframe&gt;&lt;script type="text/javascript"&gt;
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</html><description>Strings and string operations are very widely used, particularly in applications that involve text, speech or sequences. Yet the vast majority of probabilistic models contain only numerical random variables, not strings. In this paper, we show how belief propagation can be applied to do inference in models with string random variables which use common string [&hellip;]</description></oembed>
