{"id":3902,"date":"2023-04-11T09:24:21","date_gmt":"2023-04-11T09:24:21","guid":{"rendered":"https:\/\/www.stat.matf.bg.ac.rs\/?p=3902"},"modified":"2023-04-14T13:42:22","modified_gmt":"2023-04-14T13:42:22","slug":"%d1%81%d0%b5%d0%bc%d0%b8%d0%bd%d0%b0%d1%80-%d0%ba%d0%b0%d1%82%d0%b5%d0%b4%d1%80%d0%b5-%d0%b7%d0%b0-%d0%b2%d0%b5%d1%80%d0%be%d0%b2%d0%b0%d1%82%d0%bd%d0%be%d1%9b%d1%83-%d0%b8-%d1%81%d1%82%d0%b0%d1%82-2","status":"publish","type":"post","link":"https:\/\/www.stat.matf.bg.ac.rs\/en\/%d1%81%d0%b5%d0%bc%d0%b8%d0%bd%d0%b0%d1%80-%d0%ba%d0%b0%d1%82%d0%b5%d0%b4%d1%80%d0%b5-%d0%b7%d0%b0-%d0%b2%d0%b5%d1%80%d0%be%d0%b2%d0%b0%d1%82%d0%bd%d0%be%d1%9b%d1%83-%d0%b8-%d1%81%d1%82%d0%b0%d1%82-2\/","title":{"rendered":"\u0421\u0435\u043c\u0438\u043d\u0430\u0440 \u041a\u0430\u0442\u0435\u0434\u0440\u0435 \u0437\u0430 \u0432\u0435\u0440\u043e\u0432\u0430\u0442\u043d\u043e\u045b\u0443 \u0438 \u0441\u0442\u0430\u0442\u0438\u0441\u0442\u0438\u043a\u0443, 18. \u0430\u043f\u0440\u0438\u043b 2023"},"content":{"rendered":"<div data-elementor-type=\"wp-post\" data-elementor-id=\"3902\" class=\"elementor elementor-3902\">\n\t\t\t\t\t\t<section class=\"elementor-section elementor-top-section elementor-element elementor-element-6c2e9851 elementor-section-boxed elementor-section-height-default elementor-section-height-default\" data-id=\"6c2e9851\" data-element_type=\"section\" data-e-type=\"section\">\n\t\t\t\t\t\t<div class=\"elementor-container elementor-column-gap-default\">\n\t\t\t\t\t<div class=\"elementor-column elementor-col-100 elementor-top-column elementor-element elementor-element-477eccbe\" data-id=\"477eccbe\" data-element_type=\"column\" data-e-type=\"column\">\n\t\t\t<div class=\"elementor-widget-wrap elementor-element-populated\">\n\t\t\t\t\t\t<div class=\"elementor-element elementor-element-683fc526 elementor-widget elementor-widget-text-editor\" data-id=\"683fc526\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t\t\t\n<p class=\"wp-block-paragraph\">\u0423 \u0443\u0442\u043e\u0440\u0430\u043a, 18. \u0430\u043f\u0440\u0438\u043b\u0430 2023 \u0443 17:15,  \u0443 \u0441\u0430\u043b\u0438 840, \u0431\u0438\u045b\u0435 \u043e\u0434\u0440\u0436\u0430\u043d\u043e \u043f\u0440\u0435\u0434\u0430\u0432\u0430\u045a\u0435: \u041c\u0438\u043b\u0435\u043d\u0430 \u0412\u0443\u043b\u0435\u0442\u0438\u045b (\u0423\u043d\u0438\u0432\u0435\u0440\u0437\u0438\u0442\u0435\u0442 \u0443 \u041e\u043a\u0441\u0444\u043e\u0440\u0434\u0443): <strong>Fin-GAN: FORECASTING AND CLASSIFYING FINANCIAL TIME SERIES VIA GENERATIVE ADVERSARIAL NETWORKS<\/strong><\/p>\n\n\n\n<p class=\"wp-block-paragraph\">\u0420\u0435\u0437\u0438\u043c\u0435: We investigate the use of Generative Adversarial Networks (GANs) for probabilistic forecasting of financial time series. <\/p><\/div><\/div><\/div><\/div><\/div><\/section><\/div> <a href=\"https:\/\/www.stat.matf.bg.ac.rs\/en\/%d1%81%d0%b5%d0%bc%d0%b8%d0%bd%d0%b0%d1%80-%d0%ba%d0%b0%d1%82%d0%b5%d0%b4%d1%80%d0%b5-%d0%b7%d0%b0-%d0%b2%d0%b5%d1%80%d0%be%d0%b2%d0%b0%d1%82%d0%bd%d0%be%d1%9b%d1%83-%d0%b8-%d1%81%d1%82%d0%b0%d1%82-2\/#more-3902\" class=\"more-link elementor-more-link\"><span aria-label=\"Continue reading \u0421\u0435\u043c\u0438\u043d\u0430\u0440 \u041a\u0430\u0442\u0435\u0434\u0440\u0435 \u0437\u0430 \u0432\u0435\u0440\u043e\u0432\u0430\u0442\u043d\u043e\u045b\u0443 \u0438 \u0441\u0442\u0430\u0442\u0438\u0441\u0442\u0438\u043a\u0443, 18. \u0430\u043f\u0440\u0438\u043b 2023\">(more&hellip;)<\/span><\/a>","protected":false},"excerpt":{"rendered":"<p>\u0423 \u0443\u0442\u043e\u0440\u0430\u043a, 18. \u0430\u043f\u0440\u0438\u043b\u0430 2023 \u0443 17:15, \u0443 \u0441\u0430\u043b\u0438 840, \u0431\u0438\u045b\u0435 \u043e\u0434\u0440\u0436\u0430\u043d\u043e \u043f\u0440\u0435\u0434\u0430\u0432\u0430\u045a\u0435: \u041c\u0438\u043b\u0435\u043d\u0430 \u0412\u0443\u043b\u0435\u0442\u0438\u045b (\u0423\u043d\u0438\u0432\u0435\u0440\u0437\u0438\u0442\u0435\u0442 \u0443 \u041e\u043a\u0441\u0444\u043e\u0440\u0434\u0443): Fin-GAN: FORECASTING AND CLASSIFYING FINANCIAL TIME SERIES VIA GENERATIVE ADVERSARIAL NETWORKS \u0420\u0435\u0437\u0438\u043c\u0435: We investigate the use of Generative Adversarial Networks (GANs) for probabilistic forecasting of financial time series.<\/p>","protected":false},"author":4,"featured_media":0,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[1],"tags":[],"class_list":["post-3902","post","type-post","status-publish","format-standard","hentry","category-uncategorized"],"blocksy_meta":[],"_links":{"self":[{"href":"https:\/\/www.stat.matf.bg.ac.rs\/en\/wp-json\/wp\/v2\/posts\/3902","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/www.stat.matf.bg.ac.rs\/en\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/www.stat.matf.bg.ac.rs\/en\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/www.stat.matf.bg.ac.rs\/en\/wp-json\/wp\/v2\/users\/4"}],"replies":[{"embeddable":true,"href":"https:\/\/www.stat.matf.bg.ac.rs\/en\/wp-json\/wp\/v2\/comments?post=3902"}],"version-history":[{"count":14,"href":"https:\/\/www.stat.matf.bg.ac.rs\/en\/wp-json\/wp\/v2\/posts\/3902\/revisions"}],"predecessor-version":[{"id":3961,"href":"https:\/\/www.stat.matf.bg.ac.rs\/en\/wp-json\/wp\/v2\/posts\/3902\/revisions\/3961"}],"wp:attachment":[{"href":"https:\/\/www.stat.matf.bg.ac.rs\/en\/wp-json\/wp\/v2\/media?parent=3902"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/www.stat.matf.bg.ac.rs\/en\/wp-json\/wp\/v2\/categories?post=3902"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/www.stat.matf.bg.ac.rs\/en\/wp-json\/wp\/v2\/tags?post=3902"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}