{"id":39260,"date":"2018-04-23T00:00:59","date_gmt":"2018-04-22T16:00:59","guid":{"rendered":"https:\/\/case.ntu.edu.tw\/blog\/?p=39260"},"modified":"2022-01-05T02:11:01","modified_gmt":"2022-01-04T18:11:01","slug":"%e9%9d%a2%e5%b0%8d%e5%a6%82%e5%90%8c%e9%bb%91%e7%9b%92%e5%ad%90%e7%9a%84%e7%a5%9e%e7%b6%93%e7%b6%b2%e8%b7%af%ef%bc%8cai%e7%a7%91%e5%ad%b8%e5%ae%b6%e5%a6%82%e4%bd%95%e5%8e%bb%e8%a7%a3%e9%87%8b%e5%85%a7","status":"publish","type":"post","link":"https:\/\/case.ntu.edu.tw\/blog\/?p=39260","title":{"rendered":"\u9762\u5c0d\u5982\u540c\u9ed1\u76d2\u5b50\u7684\u795e\u7d93\u7db2\u8def\uff0cAI\u79d1\u5b78\u5bb6\u5982\u4f55\u53bb\u89e3\u91cb\u5167\u5728\u6a5f\u5236\uff1f"},"content":{"rendered":"<div class=\"single-post-media clr\">\n<div class=\"post-thumbnail\"><img fetchpriority=\"high\" decoding=\"async\" src=\"https:\/\/highscope.ch.ntu.edu.tw\/wordpress\/wp-content\/uploads\/2018\/04\/p78448p1.png\" alt=\"\u9762\u5c0d\u5982\u540c\u9ed1\u76d2\u5b50\u7684\u795e\u7d93\u7db2\u8def\uff0cAI\u79d1\u5b78\u5bb6\u5982\u4f55\u53bb\u89e3\u91cb\u5167\u5728\u6a5f\u5236\uff1f\" width=\"450\" height=\"338\" \/><\/div>\n<\/div>\n<div class=\"entry clr\">\n<div class=\"pf-content\">\n<p><strong>\u7de8\u8b6f\uff0f\u845b\u7ad1\u5fd7<\/strong><\/p>\n<p>\u4f4d\u5728\u52a0\u5dde\u7684Uber\u7e3d\u90e8\uff0cYosinski\u50cf\u8a31\u591aAI\u79d1\u5b78\u5bb6\u4e00\u6a23\uff0c\u60f3\u8fa6\u6cd5\u8981\u628a\u6df1\u5ea6\u5b78\u7fd2(Deep Learning)\u61c9\u7528\u5728\u4ed6\u5011\u7684\u81ea\u99d5\u7cfb\u7d71\u4e0a\u3002\u5c07\u5927\u91cf\u5df2\u6a19\u8a18\u7684\u5f71\u50cf\uff0c\u50cf\u662f\u6591\u99ac\u3001\u6d88\u9632\u8eca\u3001\u5b89\u5168\u5e36\u7b49\u62ff\u4f86\u8a13\u7df4\u51fa\u4e00\u500b\u80fd\u5920\u8fa8\u8b58\u7269\u9ad4\u7684\u6a21\u578b\u4e4b\u5f8c\uff0c\u4ed6\u5728\u60f3\u9019\u6a23\u7684\u6a21\u578b\u662f\u5426\u4e5f\u80fd\u5920\u8a8d\u51fa\u93e1\u982d\u524d\u7684\u81ea\u5df1\uff1fYosinski\u5c07\u651d\u5f71\u6a5f\u8f49\u5411\u81ea\u5df1\u4e00\u770b\uff0c\u4ee4\u4eba\u610f\u5916\u7684\u662f\uff0c\u67d0\u5e7e\u500b\u795e\u7d93\u7db2\u8def(Neural network)\u7684\u7bc0\u9ede(Neuron)\u4e0a\u9084\u771f\u80fd\u770b\u5230\u81ea\u5df1\u81c9\u7684\u8f2a\u5ed3\u3002<span id=\"more-78448\"><\/span><\/p>\n<p>\u597d\u5947\u7684\u4ed6\u9084\u505a\u4e86\u5e7e\u500b\u5be6\u9a57\uff0c\u767c\u73fe\u5404\u500b\u7bc0\u9ede\u64c5\u9577\u8a8d\u5f97\u7684\u6771\u897f\u4e0d\u592a\u4e00\u6a23\uff0c\u6709\u4e9b\u5f88\u6703\u8fa8\u8b58\u8eab\u4e0a\u7684\u8863\u670d\uff0c\u6709\u4e9b\u5247\u662f\u66f8\u4e0a\u7684\u6587\u5b57\uff0c\u9019\u4e9b\u4e8b\u60c5\u4e26\u6c92\u6709\u4eba\u544a\u8a34\u9019\u584a\u6a21\u578b\u53bb\u5b78\u7fd2\uff0c\u90a3\u5b83\u5230\u5e95\u662f\u5982\u4f55\u61c2\u5f97\u53bb\u8a8d\u5f97\u9019\u4e9b\u6771\u897f\u5462\uff1f\u300c\u6211\u5011\u4e0d\u662f\u975e\u5e38\u4e86\u89e3\u5b83\u5011\uff0c\u800c\u4e14\u6211\u5011\u5c0dAI\u7684\u8a8d\u77e5\u5dee\u8ddd\u6b63\u8d8a\u4f86\u8d8a\u5927\u3002\u300d\u4ed6\u9019\u9ebc\u8aaa\u3002<sup>[1]<\/sup><\/p>\n<p>\u8fd1\u5e74\u4f86\uff0c\u6df1\u5ea6\u5b78\u7fd2\u5df2\u70ba\u8a31\u591a\u8de8\u9818\u57df\u79d1\u5b78\u7814\u7a76\u6ce8\u5165\u5927\u91cf\u6d3b\u6c34\uff0c\u4e5f\u70ba\u73fe\u4ee3\u79d1\u6280\u958b\u555f\u4e86\u66f4\u591a\u7684\u53ef\u80fd\u6027\u3002\u7136\u800c\uff0c\u8907\u96dc\u7684\u795e\u7d93\u7db2\u8def\u5c31\u5982\u540c\u4e00\u584a\u9ed1\u76d2\u5b50\uff0c\u5728\u59cb\u7d42\u96e3\u4ee5\u5f9e\u5916\u90e8\u53bb\u4e86\u89e3\u5176\u4e2d\u539f\u7406\u7684\u60c5\u6cc1\u4e0b\uff0c\u66f4\u4e5f\u8003\u9a57\u8457\u4eba\u5011\u5c0d\u65bcAI\u7684\u4fe1\u4efb\u7a0b\u5ea6\u30022017\u5e74\uff0c\u4f86\u81ea\u4e00\u9805\u6b50\u76df\u7684\u6307\u793a\uff0c\u8981\u6c42\u4efb\u4f55\u6c7a\u7b56\u53ef\u80fd\u5f71\u97ff\u516c\u773e\u5229\u76ca\u7684\u516c\u53f8\u5c07\u4f86\u5fc5\u9808\u8981\u8aaa\u660e\u5176\u9810\u6e2c\u6a21\u578b\u7684\u908f\u8f2f\uff0c\u6b64\u5916\uff0c\u7f8e\u570b\u8ecd\u65b9\u7684\u85cd\u5929\u7814\u7a76\u6a5f\u69cb\u4e5f\u5c07\u6339\u6ce8\u4e03\u5343\u842c\u7f8e\u5143\u5728\u300c\u53ef\u89e3\u91cbAI\u300d\u8a08\u756b\u4e0a(Explainable AI)\uff0c\u986f\u793a\u53bb\u7406\u89e3AI\u3001\u6253\u958b\u9ed1\u76d2\u5b50\u5df2\u662f\u500b\u8feb\u4e0d\u53ef\u5f85\u7684\u8da8\u52e2\u3002\u9019\u9580\u65b0\u7684\u5b78\u554f\uff0cYosinski\u7a31\u5b83\u53eb\u4f5c\u300cAI\u795e\u7d93\u5b78\u300d(AI Neuroscience)\u3002<\/p>\n<div id=\"attachment_78451\" class=\"wp-caption aligncenter\"><a href=\"http:\/\/highscope.ch.ntu.edu.tw\/wordpress\/wp-content\/uploads\/2018\/04\/p78448p2.png\"><img decoding=\"async\" class=\"wp-image-78451\" src=\"https:\/\/highscope.ch.ntu.edu.tw\/wordpress\/wp-content\/uploads\/2018\/04\/p78448p2.png\" alt=\"\" width=\"550\" height=\"438\" \/><\/a><\/p>\n<p class=\"wp-caption-text\">\u5716\u4e00\u3001AI\u79d1\u5b78\u5bb6\u5617\u8a66\u4ee5\u591a\u7a2e\u65b9\u5f0f\u89e3\u958b\u5b9b\u5982\u9ed1\u76d2\u5b50\u822c\u7684\u795e\u7d93\u7db2\u8def \uff08\u5716\u7247\u4f86\u6e90\uff1a\u00a0<a href=\"http:\/\/www.sciencemag.org\/news\/2017\/07\/how-ai-detectives-are-cracking-open-black-box-deep-learning\">http:\/\/www.sciencemag.org\/news\/2017\/07\/how-ai-detectives-are-cracking-open-black-box-deep-learning<\/a>\uff09<\/p>\n<\/div>\n<p><strong>\u9ed1\u76d2\u63a2\u91dd-\u6295\u5165\u8cc7\u6599\u7684\u91cd\u65b0\u7d44\u5408<\/strong><\/p>\n<p>\u5728\u8a31\u591a\u4f7f\u7528\u6df1\u5ea6\u5b78\u7fd2\u505a\u6c7a\u7b56\u7684\u7576\u4e0b\uff0c\u4f7f\u7528\u8005\u5f80\u5f80\u5c31\u662f\u6295\u5165\u8f38\u5165\u53c3\u6578\u3001\u653e\u5230\u6a21\u578b\uff0c\u6700\u5f8c\u5c31\u76f4\u63a5\u5f97\u51fa\u7d50\u679c\uff0c\u82e5\u4e8b\u5c0f\u9084\u53ef\u63a5\u53d7\uff0c\u4f46\u82e5\u9019\u500b\u6c7a\u7b56\u975e\u5e38\u4e4b\u91cd\u8981\uff0c\u90a3\u9ebc\u4e0d\u514d\u8b93\u4eba\u5f97\u53bb\u61f7\u7591\u8cc7\u6599\u5230\u5e95\u5728\u6a21\u578b\u4e2d\u626e\u6f14\u4e86\u4ec0\u9ebc\u89d2\u8272 \u3002<\/p>\n<p>\u83ef\u76db\u9813\u5927\u5b78\u7684Ribeiro\u63d0\u51faLIME(Local Interpretable Model-agnostic Explanations)\uff0c\u6216\u8a31\u80fd\u5920\u5c0d\u6b64\u4f5c\u51fa\u89e3\u91cb \u3002\u4ed6\u5011\u50c5\u50c5\u662f\u5148\u5c07\u8f38\u5165\u8cc7\u6599\u9032\u884c\u5206\u5272\uff0c\u4e26\u4f7f\u7528\u9019\u4e9b\u5340\u584a\u7d44\u5408\u9001\u5165\u6a21\u578b\uff0c\u6700\u5f8c\u6bd4\u8f03\u51fa\u54ea\u7a2e\u7d44\u5408\u6700\u80fd\u5920\u8b93\u6a21\u578b\u9810\u6e2c\u51fa\u6307\u5b9a\u7684\u7d50\u679c\u3002\u50cf\u662f\u9019\u4e00\u5f35\u5716\u7247\u88e1\u7684\u9752\u86d9\u624b\u4e0a\u62ff\u8457\u611b\u5fc3\uff0c\u6574\u5f35\u5716\u7247\u9001\u9032\u6a21\u578b\u5f8c\u88ab\u8a8d\u70ba\u662f\u9752\u86d9\u7684\u6a5f\u7387\u53ea\u67090.54\uff08\u7562\u7adf\u9084\u6709\u9752\u86d9\u672c\u9ad4\u4ee5\u5916\u7684\u96dc\u8a0a\uff09\uff0c\u4f46\u82e5\u6295\u5165\u7684\u5340\u584a\u50c5\u662f\u9752\u86d9\u982d\u90e8\uff0c\u5247\u8868\u73fe\u6703\u66f4\u597d\uff0c\u9019\u6216\u8a31\u4e5f\u8aaa\u660e\u4e86\u6a21\u578b\u5b78\u7fd2\u5230\u53bb\u8fa8\u8b58\u9752\u86d9\u982d\u90e8\u7684\u7279\u5fb5\u3002<sup>[2]<\/sup><\/p>\n<p><a href=\"http:\/\/highscope.ch.ntu.edu.tw\/wordpress\/wp-content\/uploads\/2018\/04\/p78448p3-1.png\"><img decoding=\"async\" class=\"aligncenter wp-image-78452\" src=\"https:\/\/highscope.ch.ntu.edu.tw\/wordpress\/wp-content\/uploads\/2018\/04\/p78448p3-1.png\" alt=\"\" width=\"450\" height=\"107\" \/><\/a><\/p>\n<div id=\"attachment_78453\" class=\"wp-caption aligncenter\"><a href=\"http:\/\/highscope.ch.ntu.edu.tw\/wordpress\/wp-content\/uploads\/2018\/04\/p78448p3-2.png\"><img loading=\"lazy\" decoding=\"async\" class=\"wp-image-78453\" src=\"https:\/\/highscope.ch.ntu.edu.tw\/wordpress\/wp-content\/uploads\/2018\/04\/p78448p3-2.png\" alt=\"\" width=\"450\" height=\"228\" \/><\/a><\/p>\n<p class=\"wp-caption-text\">\u5716\u4e8c\u3001LIME\u6216\u8a31\u80fd\u5c0d\u6a21\u578b\u7522\u751f\u7684\u7d50\u679c\u505a\u66f4\u597d\u7684\u89e3\u91cb \uff08\u5716\u7247\u4f86\u6e90\uff1a<a href=\"https:\/\/www.oreilly.com\/learning\/introduction-to-local-interpretable-model-agnostic-explanations-lime\">https:\/\/www.oreilly.com\/learning\/introduction-to-local-interpretable-model-agnostic-explanations-lime<\/a>\uff09<\/p>\n<\/div>\n<p><strong>\u63a7\u5236\u9ed1\u76d2\u8d70\u5411-\u5148\u5f9e\u5df2\u77e5\u4e4b\u8655\u505a\u900f\u660e\u5316<\/strong><\/p>\n<p>\u4e00\u4f4d\u5728Google GlassBox\u8a08\u756b\u7684\u4e3b\u6301\u4ebaGupta\uff0c\u66fe\u63d0\u51fa\u55ae\u8abf\u5167\u5dee\u67e5\u8868(Monotonic interpolated loolup tables)\u4f86\u63d0\u751f\u795e\u7d93\u7db2\u8def\u7684\u900f\u660e\u6027\u3002\u8a66\u60f3\u751f\u6d3b\u4e2d\u6709\u8a31\u591a\u53c3\u6578\u9593\u672c\u4f86\u5c31\u5177\u6709\u4e00\u5b9a\u7684\u76f8\u95dc\u6027\uff0c\u9019\u4e9b\u4e8b\u60c5\u82e5\u662f\u5df2\u77e5\uff0c\u4fbf\u4e0d\u9700\u8981\u518d\u900f\u904e\u795e\u7d93\u7db2\u8def\u53bb\u91cd\u65b0\u5b78\u7fd2\u7684\u3002\u8209\u4f8b\u800c\u8a00\uff0c\u4eca\u5929\u60f3\u5f9e\u4e00\u53f0\u4e8c\u624b\u8eca\u7684\u5404\u9805\u8cc7\u8a0a\u53bb\u8a08\u7b97\u5b83\u61c9\u6709\u7684\u51fa\u552e\u50f9\u503c\uff0c\u7576\u5404\u9805\u53c3\u6578\u90fd\u56fa\u5b9a\u6642\uff0c\u5100\u8868\u677f\u4e0a\u7684\u91cc\u7a0b\u6578\u5fc5\u5c07\u8207\u5176\u50f9\u503c\u6210\u55ae\u8abf\u8ca0\u76f8\u95dc\u51fd\u6578\uff0c\u9019\u662f\u5341\u5206\u76f4\u89ba\u7684\u7d50\u679c\u3002\u56de\u5230\u5be6\u969b\u9762\uff0c\u5728\u8a31\u591a\u8cc7\u6599\u91cf\u4e0d\u8db3\u6216\u96dc\u8a0a\u904e\u591a\u7684\u60c5\u5f62\u4e0b\uff0c\u795e\u7d93\u7db2\u8def\u8a13\u7df4\u7684\u6210\u6548\u4e26\u975e\u6bcf\u6b21\u90fd\u53ef\u4ee5\u5e78\u904b\u5730\u7372\u5f97\u826f\u597d\u7d50\u679c\uff0c\u82e5\u80fd\u5c07\u7279\u5b9a\u53c3\u6578\u9593\u7684\u95dc\u4fc2\u9810\u5148\u5b9a\u7fa9\u597d\uff0c\u6e1b\u5c11\u9ed1\u76d2\u7bc0\u9ede\u7684\u90e8\u5206\uff0c\u5c07\u6709\u671b\u80fd\u52a9\u65bc\u4eba\u5011\u4e86\u89e3\u6a21\u578b\u610f\u7fa9\uff0c\u4e26\u66f4\u6613\u65bc\u63a7\u5236\u6a21\u578b\u5b78\u7fd2\u7684\u8d70\u5411\u3002<sup>[3]<\/sup><\/p>\n<p><strong>\u6a5f\u5668\u770b\u5230\u7684\u548c\u6211\u5011\u4e0d\u4e00\u6a23-\u4f7f\u7528\u8907\u6578\u500b\u6a21\u578b\u4e92\u76f8\u505a\u8fa8\u8b58\u8207\u751f\u6210<\/strong><\/p>\n<p>Yosinski\u5728\u5f8c\u7e8c\u7684\u7814\u7a76\u4e2d\u5617\u8a66\u5c07\u8a13\u7df4\u597d\u7684\u795e\u7d93\u7db2\u8def\u7528\u65bc\u7522\u751f\u5f71\u50cf\u3002\u4ed6\u5011\u5c07\u5f69\u8272\u96dc\u8a0a(Colored static)\u8f38\u5165\u6a21\u578b\u4e2d\uff0c\u4e26\u56fa\u5b9a\u8f38\u51fa\u7aef\u7684\u5206\u985e\u7d50\u679c\u70ba\u300c\u706b\u5c71\u300d\uff0c\u518d\u4f86\u628a\u7126\u9ede\u653e\u5728\u7279\u5b9a\u7684\u7bc0\u9ede\u4e0a\uff0c\u900f\u904e\u5012\u50b3\u905e(Backpropagation)\u65b9\u5f0f\u53d6\u5f97\u6700\u80fd\u5920\u8b93\u8a72\u7bc0\u9ede\u6d3b\u5316(Activation)\u7684\u68af\u5ea6\u5f8c\uff0c\u518d\u758a\u52a0\u65bc\u5f69\u8272\u96dc\u8a0a\u4e0a\u3002\u8d77\u521d\u7d50\u679c\u8b93\u4eba\u5f88\u56f0\u60d1\uff0c\u56e0\u70ba\u770b\u8d77\u4f86\u9084\u662f\u5f88\u50cf\u96dc\u8a0a\uff0c\u4f46\u6216\u8a31\u5c0d\u795e\u7d93\u7db2\u8def\u4f86\u8aaa\uff0c\u9019\u5df2\u7d93\u662f\u6700\u50cf\u706b\u5c71\u7684\u4e00\u5e45\u5f71\u50cf\u4e86\u3002<sup>[1]<\/sup><\/p>\n<p>Yosinski\u7684\u5718\u968a\u4e5f\u4f7f\u7528\u751f\u6210\u5c0d\u6297\u5f0f\u7db2\u8def(GAN)\uff0c\u9664\u4e86\u4f7f\u7528\u300c\u751f\u6210\u6a21\u578b\u300d(Generator network)\u5f9e\u8a13\u7df4\u5716\u7247\u96c6\u53bb\u5408\u6210\u6307\u5b9a\u7684\u5f71\u50cf\uff0c\u66f4\u63a1\u7528\u53e6\u4e00\u500b\u300c\u5efa\u8b70\u6a21\u578b\u300d(Adversary network)\u91dd\u5c0d\u524d\u4e00\u500b\u6a21\u578b\u7522\u51fa\u7684\u5716\u7247\u53bb\u5224\u65b7\u662f\u5426\u7b26\u5408\u521d\u59cb\u671f\u671b\uff0c\u4e26\u56de\u994b\u7d66\u751f\u6210\u6a21\u578b\u7522\u51fa\u66f4\u903c\u771f\u7684\u5f71\u50cf\u3002\u4ed6\u5011\u7684\u7d50\u679c\u767c\u73fe\u8a31\u591a\u5716\u7247\u78ba\u5be6\u5408\u6210\u51fa\u903c\u771f\u7684\u706b\u5c71\u6a23\u8c8c\uff0c\u67d0\u4e9b\u6b63\u5728\u5674\u767c\u3001\u6709\u4e9b\u5247\u662f\u4f11\u6b62\u3001\u67d0\u4e9b\u5728\u767d\u5929\u3001\u6709\u4e9b\u5728\u9ed1\u591c\uff0c\u4e5f\u6709\u4e9b\u770b\u4e0d\u51fa\u662f\u4ec0\u9ebc\u3002<sup>[4]<\/sup><\/p>\n<p>\u4e8b\u5be6\u4e0a\uff0c\u5373\u4fbf\u6211\u5011\u4e0d\u5bb9\u6613\u53bb\u7406\u89e3\u6a21\u578b\u770b\u5230\u7684\u6700\u4f73\u89e3\uff08\u4f8b\u5982\u524d\u9762\u706b\u5c71\u7684\u4f8b\u5b50\uff09\uff0cGAN\u78ba\u5be6\u6709\u52a9\u65bc\u6211\u5011\u53bb\u7406\u89e3\u6a21\u578b\u5b78\u7fd2\u5230\u7684\u662f\u54ea\u4e9b\u7279\u5fb5\u3002Yosinski\u89e3\u91cb\uff0c\u67d0\u4e9b\u7d50\u679c\u7684\u932f\u8aa4\u53ef\u80fd\u4f86\u81ea\u65bc\u8a13\u7df4\u8cc7\u6599\u3001\u6a19\u8a18\u65b9\u5f0f\u6216\u662f\u795e\u7d93\u7db2\u8def\u672c\u8eab\u7684\u554f\u984c\uff0c\u91cd\u8907\u985e\u4f3c\u7684\u5be6\u9a57\u5c31\u53ef\u4ee5\u53bb\u5370\u8b49\u3001\u4e26\u8655\u7406\u554f\u984c\u6240\u5728\u3002\u300c\u9019\u4e9b\u63d0\u793a\u4e5f\u8a31\u80fd\u70baAI\u795e\u7d93\u5b78\u63d0\u4f9b\u4e00\u4e9b\u65b9\u5411\u300d\uff0c\u4ed6\u8aaa\uff0c\u300c\u9019\u9084\u53ea\u662f\u500b\u958b\u59cb\uff0c\u5c31\u50cf\u7a7a\u767d\u5730\u5716\u4e0a\u624d\u525b\u63a2\u7d22\u5b8c\u4e00\u5c0f\u90e8\u5206\u3002\u300d<\/p>\n<div id=\"attachment_78454\" class=\"wp-caption aligncenter\"><a href=\"http:\/\/highscope.ch.ntu.edu.tw\/wordpress\/wp-content\/uploads\/2018\/04\/p78448p4.png\"><img loading=\"lazy\" decoding=\"async\" class=\"wp-image-78454\" src=\"https:\/\/highscope.ch.ntu.edu.tw\/wordpress\/wp-content\/uploads\/2018\/04\/p78448p4.png\" alt=\"\" width=\"500\" height=\"543\" \/><\/a><\/p>\n<p class=\"wp-caption-text\">\u5716\u4e09\u3001GAN\u80fd\u5920\u70ba\u795e\u7d93\u7db2\u8def\u5b78\u7fd2\u5230\u7684\u6771\u897f\u63d0\u4f9b\u7dda\u7d22\u3002 \uff08\u5716\u7247\u4f86\u6e90\uff1a\u00a0<a href=\"http:\/\/www.evolvingai.org\/ppgn\">http:\/\/www.evolvingai.org\/ppgn<\/a>\uff09<\/p>\n<\/div>\n<p>\u7de8\u8b6f\u4f86\u6e90:\u00a0<a href=\"http:\/\/www.sciencemag.org\/news\/2017\/07\/how-ai-detectives-are-cracking-open-black-box-deep-learning\">How AI detectives are cracking open the black box of deep learning<\/a><\/p>\n<hr \/>\n<p><strong>\u53c3\u8003\u6587\u737b<\/strong><\/p>\n<ul>\n<li>[1] Jason Yosinski, Jeff Clune, Anh Nguyen, Thomas Fuchs, and Hod Lipson \u201c<a href=\"http:\/\/yosinski.com\/deepvis\">Understanding Neural Networks Through Deep Visualization<\/a>\u201d 2015<\/li>\n<li>[2] \u00a0<a href=\"https:\/\/www.oreilly.com\/people\/marco-tulio-ribeiro\">Marco Tulio Ribeiro<\/a><a href=\"https:\/\/www.oreilly.com\/people\/sameer-singh\">Sameer Singh<\/a><a href=\"https:\/\/www.oreilly.com\/people\/4a7ad-carlos-guestrin\">Carlos Guestrin<\/a>\u00a0<a href=\"https:\/\/www.oreilly.com\/learning\/introduction-to-local-interpretable-model-agnostic-explanations-lime\"><strong>\u201cIntroduction to Local Interpretable Model-Agnostic Explanations (LIME)\u201d<\/strong><\/a><strong>\u00a02016<\/strong><\/li>\n<li>[3]\u00a0<a href=\"https:\/\/arxiv.org\/find\/cs\/1\/au:+Gupta_M\/0\/1\/0\/all\/0\/1\">Maya Gupta<\/a>,\u00a0<a href=\"https:\/\/arxiv.org\/find\/cs\/1\/au:+Cotter_A\/0\/1\/0\/all\/0\/1\">Andrew Cotter<\/a>,\u00a0<a href=\"https:\/\/arxiv.org\/find\/cs\/1\/au:+Pfeifer_J\/0\/1\/0\/all\/0\/1\">Jan Pfeifer<\/a>,\u00a0<a href=\"https:\/\/arxiv.org\/find\/cs\/1\/au:+Voevodski_K\/0\/1\/0\/all\/0\/1\">Konstantin Voevodski<\/a>,\u00a0<a href=\"https:\/\/arxiv.org\/find\/cs\/1\/au:+Canini_K\/0\/1\/0\/all\/0\/1\">Kevin Canini<\/a>,\u00a0<a href=\"https:\/\/arxiv.org\/find\/cs\/1\/au:+Mangylov_A\/0\/1\/0\/all\/0\/1\">Alexander Mangylov<\/a>,\u00a0<a href=\"https:\/\/arxiv.org\/find\/cs\/1\/au:+Moczydlowski_W\/0\/1\/0\/all\/0\/1\">Wojtek Moczydlowski<\/a>,\u00a0<a href=\"https:\/\/arxiv.org\/find\/cs\/1\/au:+Esbroeck_A\/0\/1\/0\/all\/0\/1\">Alex van Esbroeck<\/a>\u201c<a href=\"https:\/\/arxiv.org\/abs\/1505.06378\">Monotonic Calibrated Interpolated Look-Up Tables<\/a>\u201d Journal Machine Learning Research 2016<\/li>\n<li>[4]\u00a0<a href=\"http:\/\/www.evolvingai.org\/ppgn\">Plug &amp; Play Generative Networks: Conditional Iterative Generation of Images in Latent Space. In Computer Vision and Pattern Recognition (CVPR \u201917), 2017.<\/a><\/li>\n<\/ul>\n<\/div>\n<\/div>\n","protected":false},"excerpt":{"rendered":"<p>\u7de8\u8b6f\uff0f\u845b\u7ad1\u5fd7 \u4f4d\u5728\u52a0\u5dde\u7684Uber\u7e3d\u90e8\uff0cY<\/p>\n","protected":false},"author":21,"featured_media":39261,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[3772,3293],"tags":[6238,3006,6247,5888,6248,3792,1749],"aioseo_notices":[],"jetpack_featured_media_url":"https:\/\/case.ntu.edu.tw\/blog\/wp-content\/uploads\/2022\/01\/p78448p1.png","_links":{"self":[{"href":"https:\/\/case.ntu.edu.tw\/blog\/index.php?rest_route=\/wp\/v2\/posts\/39260"}],"collection":[{"href":"https:\/\/case.ntu.edu.tw\/blog\/index.php?rest_route=\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/case.ntu.edu.tw\/blog\/index.php?rest_route=\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/case.ntu.edu.tw\/blog\/index.php?rest_route=\/wp\/v2\/users\/21"}],"replies":[{"embeddable":true,"href":"https:\/\/case.ntu.edu.tw\/blog\/index.php?rest_route=%2Fwp%2Fv2%2Fcomments&post=39260"}],"version-history":[{"count":1,"href":"https:\/\/case.ntu.edu.tw\/blog\/index.php?rest_route=\/wp\/v2\/posts\/39260\/revisions"}],"predecessor-version":[{"id":39262,"href":"https:\/\/case.ntu.edu.tw\/blog\/index.php?rest_route=\/wp\/v2\/posts\/39260\/revisions\/39262"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/case.ntu.edu.tw\/blog\/index.php?rest_route=\/wp\/v2\/media\/39261"}],"wp:attachment":[{"href":"https:\/\/case.ntu.edu.tw\/blog\/index.php?rest_route=%2Fwp%2Fv2%2Fmedia&parent=39260"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/case.ntu.edu.tw\/blog\/index.php?rest_route=%2Fwp%2Fv2%2Fcategories&post=39260"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/case.ntu.edu.tw\/blog\/index.php?rest_route=%2Fwp%2Fv2%2Ftags&post=39260"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}