{"categories":["GAN","\u30cb\u30e5\u30fc\u30e9\u30eb\u30cd\u30c3\u30c8\u30ef\u30fc\u30af","Python","TensorFlow","\u8ad6\u6587\u30e1\u30e2"],"version":"1.0","provider_name":"Hatena Blog","description":"\u8ad6\u6587 \u8457\u8005 \u80cc\u666f \u76ee\u7684\u3068\u30a2\u30d7\u30ed\u30fc\u30c1 \u63d0\u6848\u624b\u6cd5 \u53ce\u675f\u306e\u6e2c\u5b9a \u88dc\u8db3 \u8a55\u4fa1 \u7d50\u8ad6 \u5b9f\u88c5 \u5b9f\u884c\u7d50\u679c i = 0 i = 2000 \u00d7 20 i = 2000 \u00d7 40 i = 2000 \u00d7 60 i = 2000 \u00d7 80 i = 2000 \u00d7 100 i = 2000 \u00d7 120 i = 2000 \u00d7 140 i = 2000 \u00d7 160 i = 2000 \u00d7 180 i = 2000 \u00d7 200 i = 2000 \u00d7 220 i = 2000 \u00d7 240 \u6700\u7d42\u578b \u611f\u60f3 \u8ad6\u6587 https://arxiv.org/abs/1703.10717 \u8457\u8005 David Berthelot, Thomas Sc\u2026","author_name":"nogawanogawa","provider_url":"https://hatena.blog","html":"<iframe src=\"https://hatenablog-parts.com/embed?url=https%3A%2F%2Fwww.nogawanogawa.com%2Fentry%2Fbegan\" title=\"\u3010\u8ad6\u6587\u30e1\u30e2:BEGAN\u3011BEGAN: Boundary Equilibrium Generative Adversarial Networks - Re:\u30bc\u30ed\u304b\u3089\u59cb\u3081\u308bML\u751f\u6d3b\" class=\"embed-card embed-blogcard\" scrolling=\"no\" frameborder=\"0\" style=\"display: block; width: 100%; height: 190px; max-width: 500px; margin: 10px 0px;\"></iframe>","blog_title":"Re:\u30bc\u30ed\u304b\u3089\u59cb\u3081\u308bML\u751f\u6d3b","width":"100%","published":"2018-04-11 21:50:34","title":"\u3010\u8ad6\u6587\u30e1\u30e2:BEGAN\u3011BEGAN: Boundary Equilibrium Generative Adversarial Networks","image_url":"https://cdn-ak.f.st-hatena.com/images/fotolife/n/nogawanogawa/20180324/20180324172131.png","blog_url":"https://www.nogawanogawa.com/","height":"190","url":"https://www.nogawanogawa.com/entry/began","author_url":"https://blog.hatena.ne.jp/nogawanogawa/","type":"rich"}