{"id":1471,"date":"2022-02-08T04:10:00","date_gmt":"2022-02-07T19:10:00","guid":{"rendered":"https:\/\/devneko.jp\/wordpress\/?p=1471"},"modified":"2022-02-08T04:10:00","modified_gmt":"2022-02-07T19:10:00","slug":"cost-%e6%99%82%e7%b3%bb%e5%88%97%e8%a1%a8%e7%8f%be%e5%ad%a6%e7%bf%92%e3%83%95%e3%83%ac%e3%83%bc%e3%83%a0%e3%83%af%e3%83%bc%e3%82%af","status":"publish","type":"post","link":"https:\/\/devneko.jp\/wordpress\/?p=1471","title":{"rendered":"CoST: \u6642\u7cfb\u5217\u8868\u73fe\u5b66\u7fd2\u30d5\u30ec\u30fc\u30e0\u30ef\u30fc\u30af"},"content":{"rendered":"\n<ul class=\"wp-block-list\"><li><strong>CoST: Contrastive Learning of Disentangled Seasonal-Trend Representations for Time Series Forecasting\u00a0<\/strong>[35.8]<br>\u6211\u3005\u306fCoST\u3068\u3044\u3046\u65b0\u3057\u3044\u6642\u7cfb\u5217\u8868\u73fe\u5b66\u7fd2\u30d5\u30ec\u30fc\u30e0\u30ef\u30fc\u30af\u3092\u63d0\u6848\u3059\u308b\u3002 \u30b3\u30f3\u30c8\u30e9\u30b9\u30c8\u5b66\u7fd2\u6cd5\u3092\u7528\u3044\u3066\u5b63\u7bc0\u5dee\u8868\u73fe\u3092\u5b66\u7fd2\u3059\u308b\u3002 \u5b9f\u4e16\u754c\u306e\u30c7\u30fc\u30bf\u30bb\u30c3\u30c8\u306e\u5b9f\u9a13\u3067\u306f\u3001CoST\u304c\u6700\u5148\u7aef\u306e\u30e1\u30bd\u30c3\u30c9\u3092\u4e00\u8cab\u3057\u3066\u4e0a\u56de\u3063\u3066\u3044\u308b\u3053\u3068\u304c\u793a\u3055\u308c\u3066\u3044\u308b\u3002<br><a href=\"http:\/\/arxiv.org\/abs\/2202.01575v1\">\u8ad6\u6587<\/a>\u00a0\u00a0<a href=\"https:\/\/fugumt.com\/fugumt\/paper_check\/2202.01575v1\">\u53c2\u8003\u8a33\uff08\u30e1\u30bf\u30c7\u30fc\u30bf\uff09<\/a>\u00a0\u00a0<a href=\"https:\/\/fugumt.com\/fugumt\/paper\/translated\/2202.01575.pdf.html\">\u53c2\u8003\u8a33\uff08\u5168\u6587\uff09<\/a>\u00a0\u00a0(Thu, 3 Feb 2022 13:17:38 GMT)<ul><li>\u65b0\u305f\u306a\u6642\u7cfb\u5217\u8868\u73fe\u5b66\u7fd2\u65b9\u6cd5\u306e\u63d0\u6848\u3002<\/li><li>TS2Vec\u3000<a href=\"https:\/\/github.com\/yuezhihan\/ts2vec\">GitHub &#8211; yuezhihan\/ts2vec: A universal time series representation learning framework<\/a>\u3000\u3092\u4e0a\u56de\u308b\u6027\u80fd\u3068\u306e\u3053\u3068\u3002<\/li><\/ul><\/li><\/ul>\n\n\n\n<p><\/p>\n","protected":false},"excerpt":{"rendered":"<p>CoST: Contrastive Learning of Disentangled Seasonal-Trend Representations for Time Series Forecasting\u00a0[35.8]\u6211\u3005 &hellip; <a href=\"https:\/\/devneko.jp\/wordpress\/?p=1471\" class=\"more-link\"><span class=\"screen-reader-text\">&#8220;CoST: \u6642\u7cfb\u5217\u8868\u73fe\u5b66\u7fd2\u30d5\u30ec\u30fc\u30e0\u30ef\u30fc\u30af&#8221; \u306e<\/span>\u7d9a\u304d\u3092\u8aad\u3080<\/a><\/p>\n","protected":false},"author":1,"featured_media":0,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[2],"tags":[79,595],"class_list":["post-1471","post","type-post","status-publish","format-standard","hentry","category-arxiv","tag-contrastive-learning","tag-595"],"_links":{"self":[{"href":"https:\/\/devneko.jp\/wordpress\/index.php?rest_route=\/wp\/v2\/posts\/1471","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/devneko.jp\/wordpress\/index.php?rest_route=\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/devneko.jp\/wordpress\/index.php?rest_route=\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/devneko.jp\/wordpress\/index.php?rest_route=\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"https:\/\/devneko.jp\/wordpress\/index.php?rest_route=%2Fwp%2Fv2%2Fcomments&post=1471"}],"version-history":[{"count":0,"href":"https:\/\/devneko.jp\/wordpress\/index.php?rest_route=\/wp\/v2\/posts\/1471\/revisions"}],"wp:attachment":[{"href":"https:\/\/devneko.jp\/wordpress\/index.php?rest_route=%2Fwp%2Fv2%2Fmedia&parent=1471"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/devneko.jp\/wordpress\/index.php?rest_route=%2Fwp%2Fv2%2Fcategories&post=1471"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/devneko.jp\/wordpress\/index.php?rest_route=%2Fwp%2Fv2%2Ftags&post=1471"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}