{"id":26449,"date":"2021-05-22T22:30:17","date_gmt":"2021-05-22T14:30:17","guid":{"rendered":"https:\/\/swarma.org\/?p=26449"},"modified":"2021-05-22T22:30:17","modified_gmt":"2021-05-22T14:30:17","slug":"%e5%91%a8%e6%97%a5%e7%9b%b4%e6%92%ad%e4%b8%a8%e5%9f%ba%e4%ba%8e%e8%a7%82%e6%b5%8b%e6%95%b0%e6%8d%ae%e7%9a%84%e5%9b%a0%e6%9e%9c%e5%8f%91%e7%8e%b0%e7%ae%80%e4%bb%8b","status":"publish","type":"post","link":"https:\/\/swarma.org\/?p=26449","title":{"rendered":"\u5468\u65e5\u76f4\u64ad\u4e28\u57fa\u4e8e\u89c2\u6d4b\u6570\u636e\u7684\u56e0\u679c\u53d1\u73b0\u7b80\u4ecb"},"content":{"rendered":"
\n
\n
\n

<\/p>\n

\n
\n
\n
\n
\n
\n

<\/section>\n<\/section>\n
\n
\n

\u5bfc\u8bed<\/strong><\/p>\n<\/section>\n<\/section>\n

\n

<\/section>\n<\/section>\n<\/section>\n<\/section>\n<\/section>\n
\n
\n
\n

\u672c\u671f\u5206\u4eab\uff0c\u6211\u4eec\u5c06\u4e00\u8d77\u9605\u8bfbElements of Causal Inference \u8fd9\u672c\u4e66\u7684\u7b2c\u56db\u7ae0\u548c\u7b2c\u4e03\u7ae0\uff0c\u8865\u5145\u56e0\u679c\u53d1\u73b0\u9886\u57df\u7684\u57fa\u7840\u77e5\u8bc6\u3002\u63a2\u8ba8\u591a\u53d8\u91cf\u56e0\u679c\u6a21\u578b\u548c\u53cc\u53d8\u91cf\u56e0\u679c\u6a21\u578b\u7684\u53ef\u8bc6\u522b\u6027\u95ee\u9898\uff0c\u548c\u76f8\u5e94\u7684\u4e00\u4e9b\u7ecf\u5178\u7684\u56e0\u679c\u53d1\u73b0\u7b97\u6cd5\uff0c\u5305\u62ec\u4f46\u4e0d\u9650\u4e8e\u591a\u53d8\u91cf\u6a21\u578b\u4e2d\u57fa\u4e8e\u7ea6\u675f\u7684\u65b9\u6cd5\u3001\u57fa\u4e8e\u6253\u5206\u51fd\u6570\u7684\u65b9\u6cd5\uff0c\u53cc\u53d8\u91cf\u6a21\u578b\u4e2d\u57fa\u4e8e\u52a0\u6027\u566a\u58f0\u6a21\u578b\u3001\u4fe1\u606f\u51e0\u4f55\uff08Information-Geometric Causal Inference\uff09\u7b49\u65b9\u6cd5\u3002<\/strong><\/p>\n


<\/p>\n

\u96c6\u667a\u4ff1\u4e50\u90e8\u8054\u5408\u667a\u6e90\u793e\u533a\uff0c\u7ec4\u7ec7\u56e0\u679c\u79d1\u5b66\u7cfb\u5217\u8bfb\u4e66\u4f1a\u7b2c\u4e8c\u5b63<\/a>\uff0c\u4ece\u57fa\u7840\u548c\u5b9e\u64cd\u89d2\u5ea6\u51fa\u53d1\uff0c\u7cbe\u8bfb\u4e24\u672c\u56e0\u679c\u79d1\u5b66\u65b9\u5411\u7684\u5165\u95e8\u6559\u6750\u3002\u8be6\u60c5\u89c1\u6587\u672b\u3002<\/strong><\/strong><\/p>\n<\/section>\n<\/section>\n<\/section>\n

\n
<\/svg><\/section>\n<\/section>\n<\/section>\n<\/section>\n<\/section>\n<\/section>\n
\n
<\/section>\n<\/section>\n


<\/p>\n

\n
\n
\n

<\/section>\n

<\/section>\n
\n
<\/svg><\/section>\n<\/section>\n<\/section>\n
\n

\u5185\u5bb9\u7b80\u4ecb<\/strong><\/strong><\/p>\n<\/section>\n

\n

<\/section>\n

<\/section>\n<\/section>\n<\/section>\n<\/section>\n

<\/section>\n

\u56e0\u679c\u5173\u7cfb\u4e00\u76f4\u662f\u4eba\u7c7b\u8ba4\u8bc6\u4e16\u754c\u7684\u57fa\u672c\u65b9\u5f0f\u548c\u73b0\u4ee3\u79d1\u5b66\u7684\u57fa\u77f3\u3002\u7231\u56e0\u65af\u5766\u5c31\u66fe\u6307\u51fa\uff0c\u897f\u65b9\u79d1\u5b66\u7684\u53d1\u5c55\u662f\u4ee5\u4e24\u4e2a\u4f1f\u5927\u7684\u6210\u5c31\u4e3a\u57fa\u7840\uff1a\u5e0c\u814a\u54f2\u5b66\u5bb6\u53d1\u660e\u5f62\u5f0f\u903b\u8f91\u4f53\u7cfb\uff0c\u4ee5\u53ca\u901a\u8fc7\u7cfb\u7edf\u7684\u5b9e\u9a8c\u53d1\u73b0\u6709\u53ef\u80fd\u627e\u51fa\u56e0\u679c\u5173\u7cfb\u3002\u4ece\u4e0e\u76f8\u5173\u5173\u7cfb\u5bf9\u6bd4\u7684\u89d2\u5ea6\u6765\u770b\uff0c\u56e0\u679c\u5173\u7cfb\u4e25\u683c\u533a\u5206\u4e86\u201c\u539f\u56e0\u201d\u53d8\u91cf\u548c\u201c\u7ed3\u679c\u201d\u53d8\u91cf\uff0c\u5728\u63ed\u793a\u4e8b\u7269\u53d1\u751f\u673a\u5236\u3001\u6307\u5bfc\u5e72\u9884\u884c\u4e3a\u7b49\u65b9\u9762\u6709\u76f8\u5173\u5173\u7cfb\u4e0d\u80fd\u66ff\u4ee3\u7684\u91cd\u8981\u4f5c\u7528\u3002\u4f8b\u5982\uff0c\u5438\u70df\u3001\u9ec4\u7259\u90fd\u4e0e\u80ba\u764c\u5177\u6709\u8f83\u5f3a\u7684\u76f8\u5173\u5173\u7cfb\uff0c\u7136\u800c\u53ea\u6709\u5438\u70df\u624d\u662f\u80ba\u764c\u7684\u539f\u56e0\uff0c\u4e5f\u53ea\u6709\u6212\u70df\u624d\u80fd\u964d\u4f4e\u80ba\u764c\u7684\u53d1\u75c5\u6982\u7387\uff0c\u800c\u628a\u7259\u9f7f\u6d17\u767d\u5219\u4e0d\u80fd\u964d\u4f4e\u80ba\u764c\u7684\u53d1\u75c5\u6982\u7387\u3002<\/span><\/p>\n


<\/span><\/p>\n

\u90a3\u4e48\uff0c\u6211\u4eec\u5982\u4f55\u63a8\u65ad\u4e8b\u7269\u4e4b\u95f4\u7684\u56e0\u679c\u5173\u7cfb\u5462\uff1f\u867d\u7136\u968f\u673a\u5e72\u9884\u5b9e\u9a8c\u662f\u6700\u76f4\u63a5\u7684\u89e3\u51b3\u65b9\u6cd5\uff0c\u4f46\u7531\u4e8e\u5b9e\u9a8c\u6280\u672f\u5c40\u9650\u3001\u5b9e\u9a8c\u8017\u8d39\u4ee3\u4ef7\u5de8\u5927\u7b49\u539f\u56e0\uff0c\u8d8a\u6765\u8d8a\u591a\u7684\u56e0\u679c\u63a8\u65ad\u9886\u57df\u5b66\u8005\u5e0c\u671b\u901a\u8fc7\u89c2\u5bdf\u6570\u636e\u63a8\u65ad\u53d8\u91cf\u4e4b\u95f4\u7684\u56e0\u679c\u5173\u7cfb\uff0c\u662f\u5f53\u524d\u56e0\u679c\u5173\u7cfb\u53d1\u73b0\u9886\u57df\u7684\u7814\u7a76\u70ed\u70b9\u3002\u56e0\u679c\u6027\u5b66\u4e60\u5219\u4f53\u73b0\u4e86\u56e0\u679c\u6027\u601d\u60f3\u5bf9\u4e8e\u673a\u5668\u5b66\u4e60\u7b97\u6cd5\u8bbe\u8ba1\u7684\u6307\u5bfc\u4f5c\u7528\u3002\u968f\u7740\u4eba\u5de5\u667a\u80fd\u7684\u53d1\u5c55\uff0c\u8d8a\u6765\u8d8a\u591a\u5b66\u8005\u5f00\u59cb\u8ba4\u8bc6\u5230\u56e0\u679c\u63a8\u65ad\u5bf9\u4e8e\u514b\u670d\u73b0\u6709\u6df1\u5ea6\u5b66\u4e60\u3001\u673a\u5668\u5b66\u4e60\u5728\u62bd\u8c61\u3001\u63a8\u7406\u3001\u53ef\u89e3\u91ca\u6027\u7b49\u65b9\u9762\u7684\u4e0d\u8db3\u5177\u6709\u91cd\u8981\u610f\u4e49\u3002\u6b63\u5982\u56fe\u7075\u5956\u5f97\u5956\u8005Pearl Judea\u63d0\u51fa\u7684 \u201c\u56e0\u679c\u5173\u7cfb\u4e4b\u68af\u201d \u4e2d\u7279\u522b\u6307\u51fa\uff0c\u6211\u4eec\u5f53\u524d\u7684\u673a\u5668\u5b66\u4e60\u53ea\u5904\u4e8e\u7b2c\u4e00\u5c42\uff0c\u53ea\u662f\u201c\u5f31\u4eba\u5de5\u667a\u80fd\u201d\uff0c\u8981\u5b9e\u73b0\u201c\u5f3a\u4eba\u5de5\u667a\u80fd\u201d\u8fd8\u9700\u8981\u5e72\u9884\u548c\u53cd\u4e8b\u5b9e\u63a8\u7406\u3002\u6240\u4ee5\uff0c\u5982\u4f55\u5c06\u56e0\u679c\u6027\u601d\u60f3\u878d\u5165\u673a\u5668\u5b66\u4e60\u6846\u67b6\uff0c\u662f\u4e00\u4e2a\u5f00\u653e\u5e76\u6781\u5177\u6311\u6218\u7684\u95ee\u9898\uff0c\u9700\u8981\u6211\u4eec\u4e00\u8d77\u6765\u63a2\u7d22\u3002<\/span><\/p>\n


<\/p>\n


<\/p>\n

\n
\n
\n

<\/section>\n

<\/section>\n
\n
<\/svg><\/section>\n<\/section>\n<\/section>\n
\n

\u4e3b\u8bb2\u4ecb\u7ecd<\/strong><\/strong><\/p>\n<\/section>\n

\n

<\/section>\n

<\/section>\n<\/section>\n<\/section>\n<\/section>\n


<\/p>\n

<\/span><\/h2>\n

<\/p>\n

\u5f20\u5929\u5065<\/span><\/strong>\uff0c\u672c\u79d1\u6bd5\u4e1a\u4e8e\u897f\u5b89\u4ea4\u901a\u5927\u5b66\uff0c\u73b0\u4e3a\u9999\u6e2f\u4e2d\u6587\u5927\u5b66\uff08\u6df1\u5733\uff09\u8ba1\u7b97\u673a\u4fe1\u606f\u5de5\u7a0b\u4e13\u4e1a\u535a\u58eb\u7814\u7a76\u751f\uff0c\u7814\u7a76\u5174\u8da3\u5305\u62ec\u53ef\u89e3\u91ca\u673a\u5668\u5b66\u4e60\u3001\u56e0\u679c\u63a8\u65ad\u53ca\u5176\u5728\u901a\u4fe1\u3001\u533b\u7597\u7b49\u9886\u57df\u4e2d\u7684\u5e94\u7528\u3002<\/span><\/p>\n


<\/p>\n

\u53c2\u8003\u6587\u732e<\/span><\/strong><\/span><\/h2>\n

[1] Peters, Jonas, Dominik Janzing, and Bernhard Sch\u00f6lkopf. Elements of causal inference: foundations and learning algorithms. The MIT Press, 2017.<\/span><\/p>\n

[2] Mooij, Joris M., et al. “Distinguishing cause from effect using observational data: methods and benchmarks.” The Journal of Machine Learning Research 17.1 (2016): 1103-1204.<\/span><\/p>\n

[3] \u8521\u745e\u521d, \u90dd\u5fd7\u5cf0. \u5927\u6570\u636e\u4e2d\u7684\u56e0\u679c\u5173\u7cfb\u53d1\u73b0. \u5317\u4eac\uff1a\u79d1\u5b66\u51fa\u7248\u793e, 2018<\/span><\/p>\n

[4] Zheng, Xun, et al. “Dags with no tears: Continuous optimization for structure learning.” arXiv preprint arXiv:1803.01422 (2018).<\/span><\/p>\n

[5] Lopez-Paz D, Nishihara R, Chintala S, et al. Discovering causal signals in images[C]\/\/Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition. 2017: 6979-6987..<\/span><\/p>\n


<\/section>\n

<\/h4>\n

\u53c2\u4e0e\u65f6\u95f4\uff1a<\/span><\/strong><\/span><\/h4>\n

\u65f6\u95f4\uff1a5\u670823\u65e5\uff08\u5468\u65e5\uff09\u4e0a\u534810:00-12:00<\/span><\/p>\n


<\/p>\n

\u76f4\u64ad\u65b9\u5f0f\u4e00\uff1a\u817e\u8baf\u4f1a\u8bae\u76f4\u64ad<\/span><\/strong><\/span><\/section>\n

<\/span><\/strong><\/span><\/section>\n

<\/p>\n

\u76f4\u64ad\u5730\u5740\uff1a<\/span>https:\/\/meeting.tencent.com\/l\/equCySYquCgU<\/span>
<\/p>\n


<\/span><\/p>\n

<\/span><\/strong><\/span><\/section>\n
\u76f4\u64ad\u65b9\u5f0f\u4e8c\uff1a\u89c6\u9891\u53f7\u76f4\u64ad<\/span><\/strong><\/span><\/section>\n
<\/mpvideosnap><\/section>\n
\u6b22\u8fce\u5173\u6ce8\u201c\u96c6\u667a\u4ff1\u4e50\u90e8\u201d\u89c6\u9891\u53f7\uff0c\u89c2\u770b\u76f4\u64ad<\/span>
<\/section>\n

<\/span><\/section>\n
 <\/span><\/section>\n

\n
\n
\n
\n
\n

\u56e0\u679c\u79d1\u5b66\u7b2c\u4e8c\u5b63\u8bfb\u4e66\u4f1a\u62a5\u540d\u4e2d<\/strong><\/p>\n<\/section>\n<\/section>\n<\/section>\n<\/section>\n


<\/section>\n<\/h2>\n
\u56e0\u679c\u63a8\u65ad\u4e0e\u673a\u5668\u5b66\u4e60\u9886\u57df\u7684\u7ed3\u5408\u5df2\u7ecf\u5438\u5f15\u4e86\u8d8a\u6765\u8d8a\u591a\u6765\u81ea\u5b66\u754c\u4e1a\u754c\u7684\u5173\u6ce8\uff0c\u4e3a\u6df1\u5165\u63a2\u8ba8\u3001\u666e\u53ca\u63a8\u5e7f\u56e0\u679c\u79d1\u5b66\u8bae\u9898\uff0c\u667a\u6e90\u793e\u533a\u643a\u624b\u96c6\u667a\u4ff1\u4e50\u90e8\u5c06\u4e3e\u529e\u7b2c\u4e8c\u5b63\u300c<\/span>\u56e0\u679c\u79d1\u5b66\u4e0eCausalAI\u8bfb\u4e66\u4f1a<\/a><\/span>\u300d\u3002\u672c\u671f\u8bfb\u4e66\u4f1a\u7740\u529b\u4e8e\u5b9e\u64cd\u6027\u3001\u57fa\u7840\u6027\uff0c\u5c06\u5e26\u9886\u5927\u5bb6\u7cbe\u8bfb\u56e0\u679c\u79d1\u5b66\u65b9\u5411\u4e24\u672c\u975e\u5e38\u53d7\u5e7f\u6cdb\u8ba4\u53ef\u7684\u5165\u95e8\u6559\u6750\u3002<\/span><\/section>\n

<\/span><\/section>\n
1. Pearl, Judea, Madelyn Glymour, and Nicholas P. Jewell. Causal inference in statistics: A primer. John Wiley & Sons, 2016.<\/span>\uff08\u672c\u4e66\u4e2d\u8bd1\u7248\u300a\u7edf\u8ba1\u56e0\u679c\u63a8\u7406\u5165\u95e8\uff08\u7ffb\u8bd1\u7248\uff09\u300b\u5df2\u7531\u9ad8\u7b49\u6559\u80b2\u51fa\u7248\u793e\u51fa\u7248\uff09<\/span><\/section>\n

<\/span><\/section>\n
2. Peters, Jonas, Dominik Janzing, and Bernhard Sch\u00f6lkopf. Elements of causal inference: foundations and learning algorithms. The MIT Press, 2017.<\/span><\/section>\n

<\/span><\/section>\n
\u8bfb\u4e66\u4f1a\u6bcf\u5468\u5c06\u8fdb\u884c\u76f4\u64ad\u8ba8\u8bba\uff0c\u8fdb\u884c\u95ee\u9898\u4ea4\u6d41\u3001\u91cd\u70b9\u6982\u5ff5\u5206\u4eab\u3001\u9605\u8bfb\u6982\u89c8\u548c\u7f16\u7a0b\u5b9e\u8df5\u5185\u5bb9\u5206\u6790\u3002\u975e\u5e38\u9002\u5408\u6709\u673a\u5668\u5b66\u4e60\u80cc\u666f\uff0c\u5e0c\u671b\u6df1\u5165\u5b66\u4e60\u56e0\u679c\u79d1\u5b66\u57fa\u7840\u77e5\u8bc6\u548c\u91cd\u8981\u6a21\u578b\u65b9\u6cd5\uff0c\u5bfb\u6c42\u89e3\u51b3\u76f8\u5173\u7814\u7a76\u95ee\u9898\u7684\u670b\u53cb\u53c2\u52a0\u3002<\/span><\/section>\n

<\/span><\/section>\n
\u76ee\u524d\u56e0\u679c\u79d1\u5b66\u8bfb\u4e66\u4f1a\u7cfb\u5217\uff0c\u5df2\u7ecf\u6709\u63a5\u8fd1400\u591a\u4f4d\u7684\u6d77\u5185\u5916\u9ad8\u6821\u79d1\u7814\u9662\u6240\u7684\u4e00\u7ebf\u79d1\u7814\u5de5\u4f5c\u8005\u4ee5\u53ca\u4e92\u8054\u7f51\u4e00\u7ebf\u4ece\u4e1a\u4eba\u5458\u53c2\u4e0e\uff0c\u5438\u5f15\u4e86\u56fd\u5185\u548c\u56fd\u9645\u4e0a\u5927\u90e8\u5206\u7684\u56e0\u679c\u79d1\u5b66\u9886\u57df\u7684\u4e13\u4e1a\u79d1\u7814\u4eba\u5458\uff0c\u5982\u679c\u4f60\u4e5f\u5bf9\u8fd9\u4e2a\u4e3b\u9898\u611f\u5174\u8da3\uff0c\u60f3\u8981\u6df1\u5ea6\u5730\u53c2\u4e0e\uff0c\u5c31\u5feb\u52a0\u5165\u6211\u4eec\u5427\uff01<\/span><\/section>\n

<\/span><\/section>\n

\u62a5\u540d\uff1a\uff08\u957f\u671f\u6709\u6548\uff09<\/span><\/strong><\/span><\/h2>\n


<\/span><\/strong><\/span><\/p>\n

<\/p>\n


<\/p>\n

\u7b2c\u4e00\u6b65\uff1a\u626b\u7801\u586b\u5199\u62a5\u540d\u4fe1\u606f\u3002<\/span><\/p>\n

\u7b2c\u4e8c\u6b65\uff1a\u4fe1\u606f\u586b\u5199\u4e4b\u540e\uff0c\u8fdb\u5165\u4ed8\u6b3e\u6d41\u7a0b\uff0c\u63d0\u4ea4\u4fdd\u8bc1\u91d1299\u5143\u3002<\/span>\uff08\u7b26\u5408\u9000\u8d39\u6761\u4ef6\u540e\u53ef\u9000\u8d39\u3002\uff09<\/span><\/p>\n

\u7b2c\u4e09\u6b65\uff1a\u6dfb\u52a0\u8d1f\u8d23\u4eba\u5fae\u4fe1\uff0c\u62c9\u5165\u5bf9\u5e94\u7684\u8bfb\u4e66\u4f1a\u8ba8\u8bba\u7fa4\u3002<\/span><\/p>\n

\u6211\u4eec\u4e5f\u4f1a\u5bf9\u6bcf\u6b21\u5206\u4eab\u7684\u5185\u5bb9\u8fdb\u884c\u5f55\u5236\uff0c\u526a\u8f91\u540e\u53d1\u5e03\u5728\u96c6\u667a\u5b66\u56ed\u7684\u5b98\u7f51\u4e0a\uff0c\u4f9b\u8bfb\u4e66\u4f1a\u6210\u5458\u56de\u770b\u3002<\/span><\/section>\n

<\/span><\/section>\n

\u76f8\u5173\u8d44\u6599\u63a8<\/span>\u8350\uff1a<\/span><\/strong><\/span><\/p>\n