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<oembed><version>1.0</version><provider_name>Glosarix</provider_name><provider_url>https://glosarix.com/en/</provider_url><author_name>Team Glosarix</author_name><author_url>https://glosarix.com/en/author/adm_glosarix/</author_url><title>Latent Factor Models - Glosarix</title><type>rich</type><width>600</width><height>338</height><html>&lt;blockquote class="wp-embedded-content" data-secret="3lM0b6rWHW"&gt;&lt;a href="https://glosarix.com/en/glossary/latent-factor-models-en/"&gt;Latent Factor Models&lt;/a&gt;&lt;/blockquote&gt;&lt;iframe sandbox="allow-scripts" security="restricted" src="https://glosarix.com/en/glossary/latent-factor-models-en/embed/#?secret=3lM0b6rWHW" width="600" height="338" title="&#x201C;Latent Factor Models&#x201D; &#x2014; Glosarix" data-secret="3lM0b6rWHW" frameborder="0" marginwidth="0" marginheight="0" scrolling="no" class="wp-embedded-content"&gt;&lt;/iframe&gt;&lt;script&gt;
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</html><description>Description: Latent Factor Models are statistical approaches that aim to identify unobservable variables, known as latent factors, that influence observed variables. These models are particularly useful in contexts where data is complex and multidimensional, allowing for the decomposition of information into more manageable components. In the realm of Multimodal Models, latent factors can capture interactions [&hellip;]</description></oembed>
