{"id":326,"date":"2013-07-17T16:00:55","date_gmt":"2013-07-17T14:00:55","guid":{"rendered":"http:\/\/195.130.121.171\/akaloger\/?page_id=326"},"modified":"2026-04-07T14:39:06","modified_gmt":"2026-04-07T14:39:06","slug":"material","status":"publish","type":"page","link":"https:\/\/kalogeratos.com\/psite\/material\/","title":{"rendered":"Material"},"content":{"rendered":"<h3><strong>Methods &#8211; Toolboxes<\/strong><\/h3>\n<ul>\n<li style=\"list-style-type: none;\">\n<ul>\n<li>\n<h4><a href=\"https:\/\/kalogeratos.com\/psite\/material\/dip-means\/\">Dip-means: clustering package<\/a><\/h4>\n<\/li>\n<li>\n<h4><a href=\"https:\/\/kalogeratos.com\/psite\/material\/lrie-dra\/\">LRIE: A greedy approach to dynamic control against epidemics<\/a><\/h4>\n<\/li>\n<li>\n<h4><strong><a href=\"https:\/\/kalogeratos.com\/psite\/material\/gsm-degroot\/\">GSM-Degroot: modeling opinion dynamics<\/a><\/strong><\/h4>\n<\/li>\n<li>\n<h4><a href=\"https:\/\/kalogeratos.com\/psite\/material\/tvi-fl-graph-learning-in-time-varying-ising-model\/\">TVI-FL: Graph learning in time-varying Ising model<\/a><\/h4>\n<\/li>\n<li>\n<h4><strong><a href=\"https:\/\/kalogeratos.com\/psite\/material\/gl-3sr-laplacian-learning\/\">GL-3SR: Laplacian learning from graph signals<\/a><br \/>\n<\/strong><\/h4>\n<\/li>\n<li>\n<h4><a href=\"https:\/\/kalogeratos.com\/psite\/material\/uniforce-clustering\/\"><strong>UniForCE clustering<\/strong><\/a><\/h4>\n<\/li>\n<li><a href=\"https:\/\/github.com\/gaetanserre\/GOB\"><strong>GOB: Global Optimization Benchmark<\/strong><\/a><\/li>\n<li><strong><a href=\"https:\/\/github.com\/gaetanserre\/LipoCons\">Global Optimization Framework (formalization code in Lean)<\/a><\/strong><\/li>\n<li><a href=\"https:\/\/github.com\/gas-abel\/MultiLayerNetViz\"><strong>Multilayer Network Visualization (MultiLayerNetViz)<\/strong><\/a><\/li>\n<li><strong><a href=\"https:\/\/github.com\/gas-abel\/MIC\">MIC: Mixture of Interacting Cascades<\/a><\/strong><\/li>\n<li><strong><a href=\"https:\/\/github.com\/eloicampagne\/GraphToolbox\">Graph Toolbox package (Time-series forecasting with GNNs)<\/a><\/strong><\/li>\n<li><strong><a href=\"https:\/\/github.com\/Gwendal-Debaussart\/mixed-diffusion-trajectory\">MDT: Multi-view diffusion geometry using intertwined diffusion trajectories<\/a><\/strong><\/li>\n<li><a href=\"https:\/\/github.com\/aymen20002005\/lime_ndt\"><strong>NDT-LIME (&#8230;under development)<\/strong><\/a><\/li>\n<li><a href=\"https:\/\/gwendal-debaussart.github.io\/polyview\/cluster\/index.html\"><strong>Multi-view spectral clustering<\/strong> <\/a><a href=\"https:\/\/github.com\/aymen20002005\/lime_ndt\"><strong>(&#8230;under development)<\/strong><\/a><\/li>\n<\/ul>\n<\/li>\n<\/ul>\n<p>&nbsp;<\/p>\n<h3><strong>Datasets<\/strong><\/h3>\n<ul>\n<li>\n<h4><a href=\"https:\/\/kalogeratos.com\/psite\/material\/the-sigfox-iot-dataset\/\"><strong>SIGFOX IoT Dataset<\/strong><\/a><\/h4>\n<\/li>\n<\/ul>\n","protected":false},"excerpt":{"rendered":"<p>Methods &#8211; Toolboxes Dip-means: clustering package LRIE: A greedy approach to dynamic control against epidemics GSM-Degroot: modeling opinion dynamics TVI-FL: Graph learning in time-varying Ising model GL-3SR: Laplacian learning from graph signals UniForCE clustering GOB: Global Optimization Benchmark Global Optimization Framework (formalization code in Lean) Multilayer Network Visualization (MultiLayerNetViz) MIC: Mixture of Interacting Cascades Graph [&hellip;]<\/p>\n","protected":false},"author":1,"featured_media":0,"parent":0,"menu_order":4,"comment_status":"closed","ping_status":"closed","template":"","meta":{"footnotes":""},"class_list":["post-326","page","type-page","status-publish","hentry"],"yoast_head":"<!-- This site is optimized with the Yoast SEO plugin v27.4 - https:\/\/yoast.com\/product\/yoast-seo-wordpress\/ -->\n<title>Argyris Kalogeratos<\/title>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link rel=\"canonical\" href=\"https:\/\/kalogeratos.com\/psite\/material\/\" \/>\n<meta property=\"og:locale\" content=\"en_US\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:description\" content=\"Methods &#8211; Toolboxes Dip-means: clustering package LRIE: A greedy approach to dynamic control against epidemics GSM-Degroot: modeling opinion dynamics TVI-FL: Graph learning in time-varying Ising model GL-3SR: Laplacian learning from graph signals UniForCE clustering GOB: Global Optimization Benchmark Global Optimization Framework (formalization code in Lean) Multilayer Network Visualization (MultiLayerNetViz) MIC: Mixture of Interacting Cascades Graph [&hellip;]\" \/>\n<meta property=\"og:url\" content=\"https:\/\/kalogeratos.com\/psite\/material\/\" \/>\n<meta property=\"og:site_name\" content=\"Argyris Kalogeratos\" \/>\n<meta property=\"article:modified_time\" content=\"2026-04-07T14:39:06+00:00\" \/>\n<meta name=\"twitter:card\" content=\"summary_large_image\" \/>\n<script type=\"application\/ld+json\" class=\"yoast-schema-graph\">{\"@context\":\"https:\\\/\\\/schema.org\",\"@graph\":[{\"@type\":\"WebPage\",\"@id\":\"https:\\\/\\\/kalogeratos.com\\\/psite\\\/material\\\/\",\"url\":\"https:\\\/\\\/kalogeratos.com\\\/psite\\\/material\\\/\",\"name\":\"\",\"isPartOf\":{\"@id\":\"https:\\\/\\\/kalogeratos.com\\\/psite\\\/#website\"},\"datePublished\":\"2013-07-17T14:00:55+00:00\",\"dateModified\":\"2026-04-07T14:39:06+00:00\",\"breadcrumb\":{\"@id\":\"https:\\\/\\\/kalogeratos.com\\\/psite\\\/material\\\/#breadcrumb\"},\"inLanguage\":\"en-US\",\"potentialAction\":[{\"@type\":\"ReadAction\",\"target\":[\"https:\\\/\\\/kalogeratos.com\\\/psite\\\/material\\\/\"]}]},{\"@type\":\"BreadcrumbList\",\"@id\":\"https:\\\/\\\/kalogeratos.com\\\/psite\\\/material\\\/#breadcrumb\",\"itemListElement\":[{\"@type\":\"ListItem\",\"position\":1,\"name\":\"Home\",\"item\":\"https:\\\/\\\/kalogeratos.com\\\/psite\\\/\"},{\"@type\":\"ListItem\",\"position\":2,\"name\":\"Material\"}]},{\"@type\":\"WebSite\",\"@id\":\"https:\\\/\\\/kalogeratos.com\\\/psite\\\/#website\",\"url\":\"https:\\\/\\\/kalogeratos.com\\\/psite\\\/\",\"name\":\"Argyris Kalogeratos\",\"description\":\"Senior Research Scientist \\\/\\\/ PhD Computer Science \\\/\\\/ Machine Learning\",\"potentialAction\":[{\"@type\":\"SearchAction\",\"target\":{\"@type\":\"EntryPoint\",\"urlTemplate\":\"https:\\\/\\\/kalogeratos.com\\\/psite\\\/?s={search_term_string}\"},\"query-input\":{\"@type\":\"PropertyValueSpecification\",\"valueRequired\":true,\"valueName\":\"search_term_string\"}}],\"inLanguage\":\"en-US\"}]}<\/script>\n<!-- \/ Yoast SEO plugin. -->","yoast_head_json":{"title":"Argyris Kalogeratos","robots":{"index":"index","follow":"follow","max-snippet":"max-snippet:-1","max-image-preview":"max-image-preview:large","max-video-preview":"max-video-preview:-1"},"canonical":"https:\/\/kalogeratos.com\/psite\/material\/","og_locale":"en_US","og_type":"article","og_description":"Methods &#8211; Toolboxes Dip-means: clustering package LRIE: A greedy approach to dynamic control against epidemics GSM-Degroot: modeling opinion dynamics TVI-FL: Graph learning in time-varying Ising model GL-3SR: Laplacian learning from graph signals UniForCE clustering GOB: Global Optimization Benchmark Global Optimization Framework (formalization code in Lean) Multilayer Network Visualization (MultiLayerNetViz) MIC: Mixture of Interacting Cascades Graph [&hellip;]","og_url":"https:\/\/kalogeratos.com\/psite\/material\/","og_site_name":"Argyris Kalogeratos","article_modified_time":"2026-04-07T14:39:06+00:00","twitter_card":"summary_large_image","schema":{"@context":"https:\/\/schema.org","@graph":[{"@type":"WebPage","@id":"https:\/\/kalogeratos.com\/psite\/material\/","url":"https:\/\/kalogeratos.com\/psite\/material\/","name":"","isPartOf":{"@id":"https:\/\/kalogeratos.com\/psite\/#website"},"datePublished":"2013-07-17T14:00:55+00:00","dateModified":"2026-04-07T14:39:06+00:00","breadcrumb":{"@id":"https:\/\/kalogeratos.com\/psite\/material\/#breadcrumb"},"inLanguage":"en-US","potentialAction":[{"@type":"ReadAction","target":["https:\/\/kalogeratos.com\/psite\/material\/"]}]},{"@type":"BreadcrumbList","@id":"https:\/\/kalogeratos.com\/psite\/material\/#breadcrumb","itemListElement":[{"@type":"ListItem","position":1,"name":"Home","item":"https:\/\/kalogeratos.com\/psite\/"},{"@type":"ListItem","position":2,"name":"Material"}]},{"@type":"WebSite","@id":"https:\/\/kalogeratos.com\/psite\/#website","url":"https:\/\/kalogeratos.com\/psite\/","name":"Argyris Kalogeratos","description":"Senior Research Scientist \/\/ PhD Computer Science \/\/ Machine Learning","potentialAction":[{"@type":"SearchAction","target":{"@type":"EntryPoint","urlTemplate":"https:\/\/kalogeratos.com\/psite\/?s={search_term_string}"},"query-input":{"@type":"PropertyValueSpecification","valueRequired":true,"valueName":"search_term_string"}}],"inLanguage":"en-US"}]}},"jetpack_sharing_enabled":true,"_links":{"self":[{"href":"https:\/\/kalogeratos.com\/psite\/wp-json\/wp\/v2\/pages\/326","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/kalogeratos.com\/psite\/wp-json\/wp\/v2\/pages"}],"about":[{"href":"https:\/\/kalogeratos.com\/psite\/wp-json\/wp\/v2\/types\/page"}],"author":[{"embeddable":true,"href":"https:\/\/kalogeratos.com\/psite\/wp-json\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"https:\/\/kalogeratos.com\/psite\/wp-json\/wp\/v2\/comments?post=326"}],"version-history":[{"count":12,"href":"https:\/\/kalogeratos.com\/psite\/wp-json\/wp\/v2\/pages\/326\/revisions"}],"predecessor-version":[{"id":2374,"href":"https:\/\/kalogeratos.com\/psite\/wp-json\/wp\/v2\/pages\/326\/revisions\/2374"}],"wp:attachment":[{"href":"https:\/\/kalogeratos.com\/psite\/wp-json\/wp\/v2\/media?parent=326"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}