1.0UNI FRhttps://www.uni.lu/frUNI FRhttps://www.uni.lu/frrich600338<blockquote class="wp-embedded-content" data-secret="6ZAue7IQMr"><a href="https://www.uni.lu/fr/news/big-data-at-the-nanoscale/">Big Data at the Nanoscale</a></blockquote><iframe sandbox="allow-scripts" security="restricted" src="https://www.uni.lu/fr/news/big-data-at-the-nanoscale/embed/#?secret=6ZAue7IQMr" width="600" height="338" title="« Big Data at the Nanoscale » — UNI FR" data-secret="6ZAue7IQMr" frameborder="0" marginwidth="0" marginheight="0" scrolling="no" class="wp-embedded-content"></iframe><script> /*! This file is auto-generated */ !function(c,d){"use strict";var e=!1,o=!1;if(d.querySelector)if(c.addEventListener)e=!0;if(c.wp=c.wp||{},c.wp.receiveEmbedMessage);else if(c.wp.receiveEmbedMessage=function(e){var t=e.data;if(!t);else if(!(t.secret||t.message||t.value));else if(/[^a-zA-Z0-9]/.test(t.secret));else{for(var r,s,a,i=d.querySelectorAll('iframe[data-secret="'+t.secret+'"]'),n=d.querySelectorAll('blockquote[data-secret="'+t.secret+'"]'),o=new RegExp("^https?:$","i"),l=0;l<n.length;l++)n[l].style.display="none";for(l=0;l<i.length;l++)if(r=i[l],e.source!==r.contentWindow);else{if(r.removeAttribute("style"),"height"===t.message){if(1e3<(s=parseInt(t.value,10)))s=1e3;else if(~~s<200)s=200;r.height=s}if("link"===t.message)if(s=d.createElement("a"),a=d.createElement("a"),s.href=r.getAttribute("src"),a.href=t.value,!o.test(a.protocol));else if(a.host===s.host)if(d.activeElement===r)c.top.location.href=t.value}}},e)c.addEventListener("message",c.wp.receiveEmbedMessage,!1),d.addEventListener("DOMContentLoaded",t,!1),c.addEventListener("load",t,!1);function t(){if(o);else{o=!0;for(var e,t,r,s=-1!==navigator.appVersion.indexOf("MSIE 10"),a=!!navigator.userAgent.match(/Trident.*rv:11\./),i=d.querySelectorAll("iframe.wp-embedded-content"),n=0;n<i.length;n++){if(!(r=(t=i[n]).getAttribute("data-secret")))r=Math.random().toString(36).substr(2,10),t.src+="#?secret="+r,t.setAttribute("data-secret",r);if(s||a)(e=t.cloneNode(!0)).removeAttribute("security"),t.parentNode.replaceChild(e,t);t.contentWindow.postMessage({message:"ready",secret:r},"*")}}}}(window,document); </script> An international team of scientists, including physicists from the University of Luxembourg, have reported a comprehensive view-point on how machine learning approaches can be used in Nanoscience to analyse and extract new insights from large data sets, and accelerate material discovery, and to guide experimental design. Moreover, they discuss some of the main physical challenging behind the realisation of tailored memristive devices for machine learning.https://www.uni.lu/wp-content/uploads/sites/11/2020/01/big_data_at_the_nanoscale.jpg800600