1.0Glosarixhttps://glosarix.com/en/Team Glosarixhttps://glosarix.com/en/author/adm_glosarix/Graph Attention Network - Glosarixrich600338<blockquote class="wp-embedded-content" data-secret="f7ZsSEdWJa"><a href="https://glosarix.com/en/glossary/graph-attention-network-en/">Graph Attention Network</a></blockquote><iframe sandbox="allow-scripts" security="restricted" src="https://glosarix.com/en/glossary/graph-attention-network-en/embed/#?secret=f7ZsSEdWJa" width="600" height="338" title="“Graph Attention Network” — Glosarix" data-secret="f7ZsSEdWJa" frameborder="0" marginwidth="0" marginheight="0" scrolling="no" class="wp-embedded-content"></iframe><script>
/*! This file is auto-generated */
!function(d,l){"use strict";l.querySelector&&d.addEventListener&&"undefined"!=typeof URL&&(d.wp=d.wp||{},d.wp.receiveEmbedMessage||(d.wp.receiveEmbedMessage=function(e){var t=e.data;if((t||t.secret||t.message||t.value)&&!/[^a-zA-Z0-9]/.test(t.secret)){for(var s,r,n,a=l.querySelectorAll('iframe[data-secret="'+t.secret+'"]'),o=l.querySelectorAll('blockquote[data-secret="'+t.secret+'"]'),c=new RegExp("^https?:$","i"),i=0;i<o.length;i++)o[i].style.display="none";for(i=0;i<a.length;i++)s=a[i],e.source===s.contentWindow&&(s.removeAttribute("style"),"height"===t.message?(1e3<(r=parseInt(t.value,10))?r=1e3:~~r<200&&(r=200),s.height=r):"link"===t.message&&(r=new URL(s.getAttribute("src")),n=new URL(t.value),c.test(n.protocol))&&n.host===r.host&&l.activeElement===s&&(d.top.location.href=t.value))}},d.addEventListener("message",d.wp.receiveEmbedMessage,!1),l.addEventListener("DOMContentLoaded",function(){for(var e,t,s=l.querySelectorAll("iframe.wp-embedded-content"),r=0;r<s.length;r++)(t=(e=s[r]).getAttribute("data-secret"))||(t=Math.random().toString(36).substring(2,12),e.src+="#?secret="+t,e.setAttribute("data-secret",t)),e.contentWindow.postMessage({message:"ready",secret:t},"*")},!1)))}(window,document);
//# sourceURL=https://glosarix.com/wp-includes/js/wp-embed.min.js
</script>
Description: A Graph Attention Network (GAT) is a type of neural network that applies attention mechanisms to data structured as graphs. These networks are particularly useful for modeling complex relationships between entities, as they allow the model to focus on specific parts of the information, thereby improving the accuracy and relevance of predictions. Unlike traditional […]