{"id":2384,"date":"2024-01-16T13:56:18","date_gmt":"2024-01-16T13:56:18","guid":{"rendered":"https:\/\/mappingcomplexity.net\/mainpage\/?p=2384"},"modified":"2024-01-23T23:20:34","modified_gmt":"2024-01-23T23:20:34","slug":"new-paper-in-nature-communications-the-d-mercator-method-for-the-multidimensional-hyperbolic-embedding-of-real-networks","status":"publish","type":"post","link":"https:\/\/mappingcomplexity.net\/mainpage\/new-paper-in-nature-communications-the-d-mercator-method-for-the-multidimensional-hyperbolic-embedding-of-real-networks\/","title":{"rendered":"New paper in Nature Communications:\u00a0The\u00a0D-Mercator method for the multidimensional hyperbolic embedding of real networks"},"content":{"rendered":"\n

We introduce\u00a0D<\/em>-Mercator<\/strong><\/a>, a model-based embedding method that produces multidimensional maps of real networks into the (D<\/em>\u2009+\u20091)-hyperbolic space, where the similarity subspace is represented as a\u00a0D<\/em>-sphere. Multidimensional representations of real networks are instrumental in the identification of factors that determine connectivity and in elucidating fundamental issues that hinge on dimensionality.<\/p>\n","protected":false},"excerpt":{"rendered":"

We introduce\u00a0D-Mercator, a model-based embedding method that produces multidimensional maps of real networks into the (D\u2009+\u20091)-hyperbolic space, where the similarity subspace is represented as a\u00a0D-sphere. Multidimensional representations of real networks are instrumental in the identification of factors that determine connectivity and in elucidating fundamental issues that hinge on dimensionality.<\/p>\n","protected":false},"author":1,"featured_media":1414,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[9],"tags":[10],"table_tags":[],"class_list":["post-2384","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-papers","tag-latest"],"yoast_head":"\nNew paper in Nature Communications:\u00a0The\u00a0D-Mercator method for the multidimensional hyperbolic embedding of real networks - Mapping Complexity Lab<\/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:\/\/mappingcomplexity.net\/mainpage\/new-paper-in-nature-communications-the-d-mercator-method-for-the-multidimensional-hyperbolic-embedding-of-real-networks\/\" \/>\n<meta property=\"og:locale\" content=\"en_US\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"New paper in Nature Communications:\u00a0The\u00a0D-Mercator method for the multidimensional hyperbolic embedding of real networks - Mapping Complexity Lab\" \/>\n<meta property=\"og:description\" content=\"We introduce\u00a0D-Mercator, a model-based embedding method that produces multidimensional maps of real networks into the (D\u2009+\u20091)-hyperbolic space, where the similarity subspace is represented as a\u00a0D-sphere. 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