{"id":48863,"date":"2024-03-13T16:40:53","date_gmt":"2024-03-13T08:40:53","guid":{"rendered":"https:\/\/swarma.org\/?p=48863"},"modified":"2024-03-13T16:40:53","modified_gmt":"2024-03-13T08:40:53","slug":"%e5%89%8d%e6%b2%bf%e8%bf%9b%e5%b1%95%ef%bc%9a%e5%88%a9%e7%94%a8%e7%a5%9e%e7%bb%8f%e7%bd%91%e7%bb%9c%e6%8f%90%e5%8f%96%e7%b3%bb%e7%bb%9f%e4%b8%ad%e6%9c%aa%e8%a2%ab%e8%a7%82%e6%b5%8b%e5%88%b0%e5%8f%98","status":"publish","type":"post","link":"https:\/\/swarma.org\/?p=48863","title":{"rendered":"\u524d\u6cbf\u8fdb\u5c55\uff1a\u5229\u7528\u795e\u7ecf\u7f51\u7edc\u63d0\u53d6\u7cfb\u7edf\u4e2d\u672a\u88ab\u89c2\u6d4b\u5230\u53d8\u91cf\u7684\u4fe1\u606f"},"content":{"rendered":"
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\u56e0\u679c\u63a8\u65ad\u65e8\u5728\u63cf\u8ff0\u7ed9\u5b9a\u53d8\u91cf\u4e4b\u95f4\u7684\u56e0\u679c\u5173\u7cfb\u3002\u7136\u800c\uff0c\u5728\u8bb8\u591a\u5b9e\u9645\u7cfb\u7edf\u4e2d\uff0c\u53d8\u91cf\u901a\u5e38\u53ea\u80fd\u90e8\u5206\u89c2\u6d4b\u5230\uff0c\u800c\u4e00\u4e9b\u672a\u89c2\u6d4b\u5230\u7684\u53d8\u91cf\u53ef\u80fd\u643a\u5e26\u91cd\u8981\u4fe1\u606f\u5e76\u5bf9\u76ee\u6807\u4ea7\u751f\u56e0\u679c\u6548\u5e94\u3002\u8bc6\u522b\u8fd9\u4e9b\u672a\u89c2\u6d4b\u5230\u7684\u539f\u56e0\u4ecd\u7136\u662f\u4e00\u4e2a\u6311\u6218\u3002\u6700\u8fd1\u8fd9\u7bc7\u53d1\u8868\u4e8e Entropy \u300c\u56e0\u679c\u4e0e\u590d\u6742\u7cfb\u7edf\u7279\u520a\u300d\u7684\u6700\u65b0\u7814\u7a76\u4f7f\u7528\u4e00\u4e2a\u540d\u4e3a\u795e\u7ecf\u56e0\u679c\u4fe1\u606f\u63d0\u53d6\u5668\uff08Neural Causal Information<\/span><\/strong> Extractor\uff0cNCIE\uff09\u7684\u751f\u6210\u5668-\u5224\u522b\u5668\u6846\u67b6\u6784\u5efa\u9690\u53d8\u91cf\uff0c\u5b83\u53ef\u4ee5\u8865\u5145\u672a\u89c2\u6d4b\u5230\u539f\u56e0\u7684\u4fe1\u606f\uff0c\u4ece\u800c\u63d0\u4f9b\u5305\u62ec\u5df2\u89c2\u6d4b\u5230\u7684\u539f\u56e0\u548c\u672a\u89c2\u5bdf\u5230\u7684\u539f\u56e0\u7684\u8868\u793a\u5728\u5185\u7684\u5b8c\u6574\u539f\u56e0\u96c6\u5408\u3002\u901a\u8fc7\u6700\u5927\u5316\u76ee\u6807\u4e0e\u5df2\u89c2\u5bdf\u5230\u7684\u539f\u56e0\u548c\u9690\u53d8\u91cf\u7684\u5e76\u96c6\u4e4b\u95f4\u7684\u4e92\u4fe1\u606f\uff0c\u751f\u6210\u7684\u9690\u53d8\u91cf\u53ef\u4ee5\u8865\u5145\u672a\u89c2\u6d4b\u5230\u7684\u539f\u56e0\u672c\u5e94\u63d0\u4f9b\u7684\u4fe1\u606f\u3002\u5408\u6210\u5b9e\u9a8c\u8868\u660e\uff0c\u9690\u53d8\u91cf\u4fdd\u7559\u4e86\u672a\u89c2\u6d4b\u5230\u7684\u539f\u56e0\u7684\u4fe1\u606f\u548c\u52a8\u529b\u5b66\u3002\u6b64\u5916\uff0c\u5e7f\u6cdb\u7684\u5b9e\u9645\u65f6\u95f4\u5e8f\u5217\u9884\u6d4b\u4efb\u52a1\u5728\u5f15\u5165\u9690\u53d8\u91cf\u540e\u663e\u793a\u51fa\u66f4\u9ad8\u7684\u7cbe\u5ea6\uff0c\u8868\u660e\u5b83\u4eec\u4e0e\u76ee\u6807\u4e4b\u95f4\u7684\u56e0\u679c\u5173\u7cfb\u3002\u672c\u6587\u662f\u8bba\u6587\u7b2c\u4e00\u4f5c\u8005\u6881\u4eac\u660a\u5bf9\u8bba\u6587\u7684\u89e3\u8bfb\u3002<\/span><\/strong><\/span><\/strong><\/section>\n

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\u8bba\u6587 [1] \u8ba4\u4e3a\uff0c\u7531\u4e8e\u56e0\u679c\u8fc7\u7a0b\u662f\u4e00\u4e2a\u4fe1\u606f\u8f6c\u79fb\u7684\u8fc7\u7a0b\uff0c\u6240\u4ee5\u76ee\u6807\u53d8\u91cf\u7684\u4fe1\u606f\u5e94\u7531\u56e0\u53d8\u91cf\u63d0\u4f9b\u3002\u5728\u65f6\u95f4\u5e8f\u5217\u4e2d\uff0c t \u65f6\u523b\u76ee\u6807\u53d8\u91cf Yt<\/sub> \u7684\u56e0\u53d8\u91cf\u5305\u62ec\u4e86\u76ee\u6807\u53d8\u91cf\u81ea\u8eab\u548c\u67d0\u4e9b\u5176\u4ed6\u53d8\u91cf\u7684\u5386\u53f2 ( Y<t <\/sub>\u548c X<t<\/sub>)\u3002\u53e6\u5916\uff0c[2] \u8ba4\u4e3a\uff0c\u4efb\u4e00\u56e0\u53d8\u91cf\u90fd\u5e94\u8be5\u7ed9\u76ee\u6807\u53d8\u91cf\u63d0\u4f9b\u4e00\u4e9b\u5176\u4ed6\u56e0\u53d8\u91cf\u65e0\u6cd5\u63d0\u4f9b\u7684\u4fe1\u606f\uff0c\u5373\u6761\u4ef6\u4e92\u4fe1\u606f I(Yt<\/sub>; X<t<\/sub> | X<t<\/span>–<\/sup><\/sub>)\u3002<\/span><\/o:p><\/section>\n

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\u5982\u679c\u628a Zt<\/sub> \u770b\u4f5c\u662f Yt<\/sub> \u7684\u8868\u5f81\u53d8\u91cf\uff0c\u8fd9\u4e2a\u95ee\u9898\u662f\u4e00\u4e2a\u6700\u5927\u5316<\/span>\uff08\u6761\u4ef6\uff09<\/span>\u4e92\u4fe1\u606f\u7684\u8868\u5f81\u5b66\u4e60\u95ee\u9898\u3002\u6700\u5927\u5316\u4e92\u4fe1\u606f\u662f\u8868\u5f81\u5b66\u4e60\u65b9\u6cd5\u6700\u91cd\u8981\u7684\u76ee\u6807\u4e4b\u4e00\uff0c\u4f46\u662f\u5982\u4f55\u6709\u6548\u4e14\u9ad8\u6548\u5730\u8861\u91cf\u76ee\u6807\u53d8\u91cf\u548c\u5176\u8868\u5f81\u4e4b\u95f4\u7684\u4e92\u4fe1\u606f\u4e00\u76f4\u662f\u4e2a\u8fd8\u6ca1\u8fbe\u81f4\u5b8c\u7f8e\u7684\u95ee\u9898\uff0c\u66f4\u522b\u8bf4\u5982\u4f55\u6700\u5927\u5316\u8fd9\u4e24\u8005\u4e4b\u95f4\u7684\u4e92\u4fe1\u606f\u3002\u6700\u8033\u719f\u80fd\u8be6\u7684\u65b9\u6cd5\u5f53\u5c5eVariational AutoEncoder <\/span>(VAE)<\/span>\uff0c\u901a\u8fc7\u8bad\u7ec3\u4ee3\u8868p(z|x)\u7684\u7f16\u7801\u5668encoder\u548cp(x|z)\u7684\u89e3\u7801\u5668decoder\u8fbe\u5230\u6700\u5927\u5316evidence lower bound<\/span> (ELBO) <\/span>\u7684\u76ee\u7684\u3002\u8fd9\u4e00\u65b9\u6cd5\u80fd\u591f\u6709\u6548\u5730\u4f7f\u8868\u5f81\u643a\u5e26\u76ee\u6807\u7684\u4fe1\u606f\uff0c\u4f46\u662f\u5b83\u4ecd\u6709\u51e0\u4e2a\u9650\u5236\uff1a1. \u65e0\u6cd5\u5904\u7406\u65f6\u5e8f\u6570\u636e\u4e2d\u7684\u65f6\u5e8f\u4fe1\u606f\uff0c2. VAE\u5047\u8bbe\u8868\u5f81\u7b26\u5408\u9ad8\u65af\u5206\u5e03\uff1b\u53c8\u6bd4\u5982 [3] \u901a\u8fc7\u6570\u636e\u7b26\u5408\u9ad8\u65af\u5206\u5e03\u7684\u5047\u8bbe\u80fd\u5f97\u51fa\u4e92\u4fe1\u606f\u7684\u89e3\u6790\u8868\u8fbe\u5f0f\uff0c\u4ece\u800c\u901a\u8fc7\u4f18\u5316\u6b64\u8868\u8fbe\u5f0f\u6765\u6700\u5927\u5316\u4e92\u4fe1\u606f\u3002\u4f46\u662f\uff0c\u548cVAE\u4e00\u6837\uff0c\u8fd9\u4e9b\u6700\u5927\u5316\u4e92\u4fe1\u606f\u7684\u65b9\u6cd5\u90fd\u53d7\u5230\u5404\u79cd\u5404\u6837\u5047\u8bbe\u7684\u9650\u5236\uff0c\u4ee5\u81f4\u65e0\u6cd5\u5728\u5e7f\u6cdb\u901a\u7528\u7684\u60c5\u51b5\u91cc\u76f4\u63a5\u4f18\u5316\u4e92\u4fe1\u606f\u3002<\/span><\/o:p><\/section>\n

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\u6709\u9274\u4e8e\u6b64\uff0c\u6211\u4eec\u5728\u770b\u5230\u4e86MINE [5] \uff0c\u4e00\u4e2a\u4f7f\u7528\u795e\u7ecf\u7f51\u7edc\u6765\u6700\u5927\u5316\u8f93\u5165\u95f4\u7684\u4e92\u4fe1\u606f\u7684\u4e0b\u754c\uff0c\u4ece\u800c\u4f30\u7b97\u4e92\u4fe1\u606f\u7684\u6846\u67b6\u65f6\u53d7\u5230\u542f\u53d1\uff1a\u65e2\u7136\u53ef\u4ee5\u5229\u7528\u795e\u7ecf\u7f51\u7edcB\u6765\u6700\u5927\u5316\u4e92\u4fe1\u606f\u7684\u4e0b\u754c\uff0c\u90a3B\u7684\u8f93\u5165\u7aef\u65e2\u53ef\u4ee5\u662f\u67d0\u4e2a\u53d8\u91cf\uff0c\u4e5f\u53ef\u4ee5\u662f\u53e6\u4e00\u4e2a\u795e\u7ecf\u7f51\u7edcA\u7684\u8f93\u51fa\u3002\u5982\u679c\u6211\u4eec\u628a\u4e24\u4e2a\u795e\u7ecf\u7f51\u7edcA\u548cB\u4e32\u8054\u8d77\u6765\uff0c\u53ef\u4ee5\u901a\u8fc7\u4f18\u5316A\u548cB\u7684\u53c2\u6570\uff0c\u6700\u5927\u5316\u67d0\u4e2a\u53d8\u91cf (Y) \u548c\u795e\u7ecf\u7f51\u7edcA\u7684\u8f93\u51fa\u4e4b\u95f4<\/span>\uff08\u8868\u5f81\uff09<\/span>\u7684\u4e92\u4fe1\u606f\u3002\u56fe\u4e8c\u4e3a\u6211\u4eec\u7684\u6846\u67b6NCIE <\/span>(Neural Causal Information <\/span>Extractor) <\/span>\u7684\u793a\u610f\u56fe\u3002<\/span><\/o:p><\/section>\n

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\u56fe<\/span><\/span>2. Neural Causal <\/span>Information Extractor\uff08NCIE\uff09\u67b6\u6784<\/span><\/section>\n

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\u6362\u4e2a\u89d2\u5ea6\u770b\uff0c\u8fd9\u5176\u5b9e\u662f\u4e00\u4e2aGenerator-Critic<\/span>\uff08\u5bf9\u5e94\u6587\u7ae0\u4e2d\u7684Generator-Discriminator\uff09<\/span>\u7684\u7ed3\u6784\uff1a\u795e\u7ecf\u7f51\u7edcA\u662f\u751f\u6210\u8868\u5f81\u7684Generator\uff0c\u800c\u8868\u5f81\u7684\u635f\u5931\u51fd\u6570\uff0c\u5373\u5bf9 Y \u7684\u4e92\u4fe1\u606f\uff0c\u5219\u7531\u8bad\u7ec3\u597d\u7684\u795e\u7ecf\u7f51\u7edcB\u63d0\u4f9b\u3002\u5728\u8bad\u7ec3\u7684\u65f6\u5019\uff0cGenerator\u4f1a\u6839\u636e\u8f93\u5165\u751f\u6210 Z \uff0c\u800c Z \u5219\u4f5c\u4e3aCritic\u7684\u8f93\u5165\u5f97\u5230Critic loss\u7684\u68af\u5ea6\uff0c\u5373\u6700\u5927\u5316\u4e92\u4fe1\u606f\u4e0b\u754c\u7684\u68af\u5ea6\u3002\u8fd9\u4e2a\u68af\u5ea6\u4e5f\u4f1a\u901a\u8fc7 Z \u53cd\u5411\u4f20\u64ad\u7ed9Generator\uff0c\u4e24\u4e2a\u795e\u7ecf\u7f51\u7edc\u7684\u53c2\u6570\u901a\u8fc7\u68af\u5ea6\u4e0b\u964d\u5b8c\u6210\u66f4\u65b0\uff1aCritic\u4f1a\u66f4\u51c6\u786e\u5730\u4f30\u8ba1\u4e92\u4fe1\u606f\uff0cGenerator\u751f\u6210\u7684\u8868\u5f81\u4f1a\u5bf9\u76ee\u6807\u53d8\u91cf\u6709\u66f4\u591a\u4e92\u4fe1\u606f\u3002<\/span><\/o:p><\/section>\n

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\u8fd9\u4e2a\u7ed3\u6784\u7684\u4f18\u70b9\u662f\u76f4\u63a5\u4f18\u5316\u4e92\u4fe1\u606f\uff0c\u800c\u4e14\u5b83\u5bf9\u4e8e\u6570\u636e\u5206\u5e03\u7684\u5047\u8bbe\u76f8\u5bf9\u8f83\u5c11<\/span><\/strong>\u3002\u8fd9\u4e2a\u6846\u67b6\u6bd4\u8f83\u65b0\u9896\uff0c\u9664\u4e86\u8fd9\u4e2a\u5de5\u4f5c\u4e4b\u5916\uff0c\u7b14\u8005\u53d1\u73b0\u540c\u671f\u6295\u7a3f\u5728NeurIPS\uff0cF.E.Rosas\u5728\u51762023\u5e7411\u6708\u53d1\u8868\u7684\u5de5\u4f5c[4]\u4e5f\u63d0\u51fa\u4e86\u76f8\u4f3c\u7684\u601d\u8def\u3002<\/span><\/o:p><\/section>\n

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\u8fd9\u4e2a\u7ed3\u6784\u4e2d\u7684Generator\u548cCritic\u4e5f\u53ef\u4ee5\u6309\u9700\u5177\u4f53\u7684\u95ee\u9898\u800c\u4f7f\u7528\u4e0d\u540c\u7684\u795e\u7ecf\u7f51\u7edc\u3002Generator\u53ef\u4ee5\u662f\u4efb\u4f55\u795e\u7ecf\u7f51\u7edc\uff0c\u6bd4\u5982CNN\uff0cRNN\uff0cLSTM\u7b49\uff1b\u800cCritic\u4e5f\u53ef\u4ee5\u662f\u4efb\u4f55\u80fd\u4f30\u7b97\u4e92\u4fe1\u606f\u7684\u795e\u7ecf\u7f51\u7edc\uff0c\u6bd4\u5982MINE [5] \u548cSMILE\u3002\u5728\u8fd9\u7bc7\u6587\u7ae0\u91cc\uff0c\u6211\u4eec\u4e3b\u8981\u8003\u8651\u7684\u662f\u4eceY<t<\/sub>\u548c X<t<\/sub>\u7684\u65f6\u5e8f\u4fe1\u606f\u5b66\u4e60\u5230 Zt<\/sub> \u7684\u8868\u5f81\uff0c\u6240\u4ee5Generator\u4f7f\u7528\u4e86RNN\uff0cCritic\u4f7f\u7528\u4e86MINE\u3002<\/span><\/o:p><\/section>\n

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\u4e0a\u8ff0\u7684\u6846\u67b6\u80fd\u751f\u6210\u4e00\u4e2a\u8868\u5f81\uff0c\u4f7f\u5f97\u8868\u5f81\u548c\u76ee\u6807\u53d8\u91cf\u7684\u4e92\u4fe1\u606f I(Y;Z) \u6700\u5927\u5316\uff0c\u4f46\u8fd8\u6ca1\u5b9e\u73b0\u6211\u4eec\u6700\u5927\u5316\u6761\u4ef6\u4e92\u4fe1\u606f I(Y;Z|X) \u7684\u76ee\u6807\u3002\u4f18\u5316\u6761\u4ef6\u4e92\u4fe1\u606f\u8981\u6bd4\u4f18\u5316\u4e92\u4fe1\u606f\u66f4\u56f0\u96be\uff0c\u56e0\u4e3a I(Y;Z|X) = I(Z;X,Y) – I(Z;X) \u9700\u8981\u540c\u65f6\u6700\u5927\u5316 I(Z;X,Y) \u548c\u6700\u5c0f\u5316 I(Z;X) \u8fd9\u4e24\u9879\u4fe1\u606f\u91cf\u3002\u76ee\u524d\u4f18\u5316\u6761\u4ef6\u4e92\u4fe1\u606f\u7684\u5de5\u4f5c\u975e\u5e38\u5c11\uff0c\u5df2\u7ecf\u53d1\u8868\u7684\u6587\u7ae0\u4e2d[6]\u6709\u5229\u7528\u6761\u4ef6\u91c7\u6837<\/span>\uff08Conditional Sampling\uff09<\/span>\u8fbe\u5230\u6700\u5927\u6761\u4ef6\u4e92\u4fe1\u606f\uff0c\u4f46\u662f\u8fd9\u79cd\u91c7\u6837\u65b9\u5f0f\u5bf9\u6570\u636e\u7684\u5206\u5e03\u548c\u5b83\u662f\u8fde\u7eed\u8fd8\u662f\u79bb\u6563\u6709\u7279\u522b\u7684\u8981\u6c42\u3002<\/span><\/o:p><\/section>\n

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\u867d\u7136\u6682\u65f6\u8fd8\u6ca1\u6709\u76f4\u63a5\u4f18\u5316 I(Y;Z|X) \u7684\u6846\u67b6\uff0c\u4f46\u662f\u5f53\u6211\u4eec\u7684\u4f18\u5316\u76ee\u6807\u662f\u5bf9 Z \u6700\u5927\u5316 I(Y;Z|X) \u65f6\uff0c\u6211\u4eec\u53d1\u73b0 I(Y;Z|X) = I(Y;X,Z) – I(Y;X) \u4e2d\u7684\u7b2c\u4e8c\u9879\u5bf9 Z \u6765\u8bf4\u662f\u5e38\u91cf\uff0c\u6240\u4ee5\u6700\u5927\u5316 I(Y;X,Z) \u4e5f\u80fd\u8fbe\u5230\u6700\u5927\u5316 I(Y;Z|X) \u7684\u76ee\u7684\u3002\u4f46\u662f\uff0c\u8fd9\u6837\u751f\u6210\u7684 Z \u867d\u7136\u80fd\u591f\u6700\u5927\u5316 I(Y;Z|X)\uff0c\u6211\u4eec\u4ecd\u65e0\u6cd5\u9650\u5236 Z \u662f\u5426\u643a\u5e26\u4e86 X \u7684\u4fe1\u606f\uff0c\u8fd9\u4e5f\u662f\u8fd9\u7bc7\u6587\u7ae0\u8fd8\u6ca1\u5b8c\u6210\u7684\u7f3a\u9677\u3002\u540e\u7eed\u6211\u4eec\u7684\u5de5\u4f5c\u4f1a\u5728\u6846\u67b6\u5185\u52a0\u4e0a\u4e00\u4e2a\u6700\u5c0f\u5316\u4fe1\u606f\u7684\u6a21\u5757\uff0c\u4ece Z \u4e2d\u5254\u9664 X \u7684\u4fe1\u606f\uff0c\u4ece\u800c\u4f7f Z \u771f\u6b63\u7684\u53ea\u8868\u5f81 X \u6ca1\u6709\u7ed9 Y \u7684\u4fe1\u606f\uff0c\u6b22\u8fce\u5404\u4f4d\u8001\u5e08\u670b\u53cb\u4eec\u5173\u6ce8\u6211\u4eec\u7684\u540e\u7eed\u5de5\u4f5c\u3002<\/span><\/o:p><\/section>\n

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\u6211\u4eec\u6784\u5efa\u4e86\u51e0\u4e2a\u7b80\u5355\u7684\u52a8\u529b\u5b66\u7cfb\u7edf\uff0c\u4e5f\u91c7\u7528\u4e86\u771f\u5b9e\u7684\u65f6\u95f4\u5e8f\u5217\u6570\u636e\u96c6<\/span>\uff08\u53d8\u7535\u5668\u6cb9\u6e29\uff0c\u8de8\u57ce\u4ea4\u901a\u5ba2\u6d41\u91cf\uff0c\u5317\u4eac\u7a7a\u6c14\u8d28\u91cf\uff09<\/span>\u6765\u9a8c\u8bc1\u6211\u4eec\u7684\u6846\u67b6\u3002\u5b9e\u9a8c\u8bc1\u660e\uff0c\u76f8\u6bd4\u5355\u72ec\u7684 X \uff0cZ \u548c X \u80fd\u7ed9 Y \u63d0\u4f9b\u5927\u90e8\u5206\u7684\u4fe1\u606f\u3002\u8fd9\u4e5f\u8bf4\u660e\u4e86\uff0c\u751f\u6210\u51fa\u6765\u7684 Z \u80fd\u591f\u5f25\u8865\u5927\u90e8\u5206 X \u6ca1\u6709\u7ed9 Y \u63d0\u4f9b\u7684\u90a3\u90e8\u5206\u4fe1\u606f\u3002<\/span><\/o:p><\/section>\n

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\u6b64\u5916\uff0cNCI<\/span>E\u53ef\u4ee5\u4f5c\u4e3a\u4e00\u4e2a\u7279\u5f81\u62bd\u53d6\u7684\u6a21\u5757\uff0c\u66f4\u597d\u7684\u62df\u5408\u548c\u8fdb\u884c\u65f6\u95f4\u5e8f\u5217\u9884\u6d4b\u7b49\u4efb\u52a1\u3002\u6211\u4eec\u7684\u5b9e\u9a8c\u8bc1\u660e\uff0cN<\/span>C<\/span>I<\/span>E<\/span>+NN\uff0cN<\/span>C<\/span>I<\/span>E<\/span>+RNN\uff0cN<\/span>C<\/span>I<\/span>E<\/span>+LSTM\u7684\u9884\u6d4b\u8bef\u5dee\u8981\u6bd4NN\uff0cRNN\uff0cLSTM\u4f4e\u3002<\/span><\/o:p><\/section>\n

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\u6881\u4eac\u660a<\/span><\/strong>\uff0c\u6e05\u534e\u5927\u5b66\u7855\u58eb\u4e8c\u5e74\u7ea7\u5728\u8bfb\uff0c\u76ee\u524d\u5728\u96c6\u667a\u4ff1\u4e50\u90e8\u505a\u79d1\u7814\u52a9\u7406\u3002\u7814\u7a76\u65b9\u5411\uff1a\u4fe1\u606f\u8bba\uff0c\u56e0\u679c\u79d1\u5b66\uff0c\u590d\u6742\u7cfb\u7edf\u3002\u6b22\u8fce\u6709\u95ee\u9898\u548c\u8ba8\u8bba\u7684\u8001\u5e08\u548c\u670b\u53cb\u901a\u8fc7\u90ae\u4ef6<\/span>liangjh22@mails.tsinghua.edu.cn<\/span>\u8d50\u6559\u3002<\/span><\/o:p><\/section>\n

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\u53c2\u8003\u6587\u732e<\/span><\/strong><\/o:p><\/h4>\n
[1]Jiang, P.; Kumar, P. Information transfer from causal history in complex system dynamics. Phys. Rev. E 2019, 99, 012306.<\/span><\/o:p><\/section>\n
[2]Spirtes, P.; Glymour, C.N.; Scheines, R. Causation, Prediction, and Search; MIT Press: Cambridge, MA, USA, 2000.<\/span><\/o:p><\/section>\n
[3]Clark, D.; Livezey, J.; Bouchard, K. Unsupervised discovery of temporal structure in noisy data with dynamical componentsanalysis. In Proceedings of the 33rd International Conference on Neural Information Processing Systems, Vancouver, BC, Canada,8\u201314 December 2019.<\/span><\/o:p><\/section>\n
[4]Christos, K.; Pedro M.; Fernando R. Learning Causally Emergent Representations. NeurIPS 2023 workshop: Information-Theoretic Principles in Cognitive Systems<\/span><\/o:p><\/section>\n
[5] Belghazi, M.I.; Baratin, A.; Rajeswar, S.; Ozair, S.; Bengio, Y.; Courville, A.; Hjelm, R.D. Mine: Mutual information neuralestimation. arXiv 2018, arXiv:1801.04062.<\/span><\/o:p><\/section>\n
[6] Wu M, Mosse M, Zhuang C, et al. Conditional negative sampling for contrastive learning of visual representations[J]. arXiv preprint arXiv:2010.02037, 2020<\/span><\/o:p><\/section>\n

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\u52a0\u5165\u56e0\u679c\u79d1\u5b66\u793e\u533a<\/strong><\/span><\/p>\n<\/section>\n<\/section>\n<\/section>\n<\/section>\n<\/section>\n


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\u968f\u7740\u201c\u56e0\u679c\u9769\u547d\u201d\u5728\u4eba\u5de5\u667a\u80fd\u4e0e\u5927\u6570\u636e\u9886\u57df\u5f90\u5f90\u5c55\u5f00\uff0c\u4f5c\u4e3a\u8fde\u63a5\u56e0\u679c\u79d1\u5b66\u4e0e\u6df1\u5ea6\u5b66\u4e60\u6865\u6881\u7684\u56e0\u679c\u8868\u5f81\u5b66\u4e60\uff0c\u6210\u4e3a\u5907\u53d7\u5173\u6ce8\u7684\u524d\u6cbf\u65b9\u5411\u3002\u4ee5\u5f80\u7684\u6df1\u5ea6\u8868\u5f81\u5b66\u4e60\u5728\u6570\u636e\u964d\u7ef4\u4e2d\u4fdd\u7559\u4fe1\u606f\u5e76\u8fc7\u6ee4\u566a\u97f3\uff0c\u65b0\u5174\u7684\u56e0\u679c\u79d1\u5b66\u5219\u5f62\u6210\u4e86\u56e0\u679c\u63a8\u7406\u4e0e\u53d1\u73b0\u7684\u4e00\u7cfb\u5217\u65b9\u6cd5\u3002\u968f\u7740\u4e8c\u8005\u7ed3\u5408\uff0c\u56e0\u679c\u8868\u5f81\u5b66\u4e60\u6709\u671b\u50ac\u751f\u66f4\u5f3a\u5927\u7684\u65b0\u4e00\u4ee3AI\u3002<\/span><\/p>\n


<\/p>\n

\u96c6\u667a\u4ff1\u4e50\u90e8\u7ec4\u7ec7\u4ee5\u201c\u56e0\u679c\u8868\u5f81\u5b66\u4e60\u201d\u4e3a\u4e3b\u9898\u7684\u8bfb\u4e66\u4f1a\uff0c\u805a\u7126\u56e0\u679c\u79d1\u5b66\u76f8\u5173\u95ee\u9898\uff0c\u5171\u5b66\u5171\u7814\u76f8\u5173\u6587\u732e\u3002\u6b22\u8fce\u4ece\u4e8b\u56e0\u679c\u79d1\u5b66\u3001\u4eba\u5de5\u667a\u80fd\u4e0e\u590d\u6742\u7cfb\u7edf\u7b49\u76f8\u5173\u7814\u7a76\u9886\u57df\uff0c\u6216\u5bf9\u56e0\u679c\u8868\u5f81\u5b66\u4e60\u7684\u7406\u8bba\u4e0e\u5e94\u7528\u611f\u5174\u8da3\u7684\u5404\u754c\u670b\u53cb\u62a5\u540d\u53c2\u4e0e\u3002\u96c6\u667a\u4ff1\u4e50\u90e8\u5df2\u7ecf\u7ec4\u7ec7\u4e09\u5b63\u201c\u56e0\u679c\u79d1\u5b66\u201d\u8bfb\u4e66\u4f1a\uff0c\u5f62\u6210\u4e86\u8d85\u8fc7\u5343\u4eba\u7684\u56e0\u679c\u79d1\u5b66\u793e\u533a\uff0c\u56e0\u679c\u8868\u5f81\u5b66\u4e60\u8bfb\u4e66\u4f1a<\/a>\u662f\u5176\u7b2c\u56db\u5b63\uff0c\u73b0\u5728\u52a0\u5165\u8bfb\u4e66\u4f1a\u5373\u53ef\u53c2\u4e0e\u56e0\u679c\u793e\u533a\u5404\u7c7b\u7ebf\u4e0a\u7ebf\u4e0b\u4ea4\u6d41\u5408\u4f5c\u3002<\/span><\/p>\n

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

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

<\/span><\/section>\n
\u8be6\u60c5\u8bf7\u89c1\uff1a<\/span><\/span><\/section>\n
\u8fde\u63a5\u56e0\u679c\u79d1\u5b66\u4e0e\u6df1\u5ea6\u5b66\u4e60\u7684\u6865\u6881\uff1a\u56e0\u679c\u8868\u5f81\u5b66\u4e60\u8bfb\u4e66\u4f1a\u542f\u52a8<\/a><\/span><\/section>\n

<\/section>\n

<\/section>\n

<\/section>\n
\n
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Entropy \u56e0\u679c\u4e0e\u590d\u6742\u7cfb\u7edf\u7279\u520a\u5f81\u7a3f\u4e2d<\/strong><\/p>\n<\/section>\n<\/section>\n<\/section>\n<\/section>\n


<\/section>\n
\u590d\u6742\u7cfb\u7edf\u65e0\u5904\u4e0d\u5728\u3002\u7cfb\u7edf\u590d\u6742\u6027\u7684\u4e00\u4e2a\u539f\u56e0\u662f\uff0c\u5927\u578b\u7cfb\u7edf\u4e2d\u4e0d\u540c\u5c42\u6b21\u4e0a\u5e7f\u6cdb\u5b58\u5728\u7ea0\u7f20\u7684\u56e0\u679c\u7ed3\u6784\u3002\u5728\u590d\u6742\u7cfb\u7edf\u4e2d\uff0c\u56e0\u679c\u5173\u7cfb\u53ef\u80fd\u662f\u6d8c\u73b0\u7684\uff0c\u8fd9\u610f\u5473\u7740\u5982\u679c\u5bf9\u7cfb\u7edf\u8fdb\u884c\u9002\u5f53\u7684\u7c97\u7c92\u5316\u64cd\u4f5c\uff0c\u90a3\u4e48\u66f4\u5f3a\u7684\u56e0\u679c\u5173\u7cfb\u53ef\u80fd\u53ea\u5728\u5b8f\u89c2\u5c42\u9762\u800c\u4e0d\u662f\u5fae\u89c2\u5c42\u9762\u89c2\u5bdf\u5f97\u5230\u3002\u66f4\u8fdb\u4e00\u6b65\uff0c\u81ea\u4e0a\u800c\u4e0b\u7684\u56e0\u679c\u5173\u7cfb\uff0c\u5373\u7cfb\u7edf\u4e2d\u7684\u5b8f\u89c2\u72b6\u6001\u53d8\u91cf\u5f71\u54cd\u5fae\u89c2\u72b6\u6001\u53d8\u91cf\uff0c\u4e5f\u53ef\u4ee5\u5728\u6d3b\u7cfb\u7edf\u6216\u793e\u4f1a\u7cfb\u7edf\u4e2d\u89c2\u5bdf\u5230\u3002<\/span><\/section>\n

<\/span><\/section>\n
\u7136\u800c\uff0c\u6211\u4eec\u5982\u4f55\u4ece\u4e00\u4e2a\u590d\u6742\u7cfb\u7edf\u7684\u539f\u59cb\u6570\u636e\u4e2d\u53d1\u73b0\u8fd9\u4e9b\u9519\u7efc\u590d\u6742\u7684\u56e0\u679c\u7ed3\u6784\u5e76\u8bc6\u522b\u56e0\u679c\u6d8c\u73b0\uff0c\u4ee5\u53ca\u5982\u4f55\u5229\u7528\u8fd9\u4e9b\u56e0\u679c\u673a\u5236\u63a8\u65ad\u7cfb\u7edf\u672a\u6765\u7684\u72b6\u6001\u548c\u6f14\u5316\uff0c\u8fd9\u4e9b\u90fd\u662f\u91cd\u8981\u800c\u53c8\u56f0\u96be\u7684\u95ee\u9898\u3002\u673a\u5668\u5b66\u4e60\u3001\u4e92\u4fe1\u606f\u5206\u89e3\u3001\u56e0\u679c\u63a8\u65ad\u7b49\u65b0\u5174\u6280\u672f\u5c06\u4e3a\u6211\u4eec\u63d0\u4f9b\u65b0\u7684\u89e3\u51b3\u65b9\u6848\u3002<\/span><\/section>\n


<\/p>\n

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<\/section>\n<\/section>\n
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Entropy \u6742\u5fd7 Causality and Complex Systems \u7279\u520a\u76ee\u524d\u5728\u6301\u7eed\u5f81\u7a3f\u4e2d\uff0c\u6b22\u8fce\u5bf9\u76f8\u5173\u8bdd\u9898\u611f\u5174\u8da3\u7684\u7814\u7a76\u8005\u6295\u7a3f\uff0c\u4f1a\u8bae\u6587\u7ae0\u4e5f\u53ef\u6295\u7a3f\u3002<\/span><\/p>\n


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

\u4e3b\u8981\u4fe1\u606f\u5982\u4e0b\uff1a<\/span><\/p>\n

\u671f\u520a\uff1aEntropy (ISSN 1099-4300)<\/span><\/p>\n

\u680f\u76ee\uff1a\u590d\u6742\u6027\u7279\u520a<\/span><\/p>\n

\u4e3b\u9898\uff1a\u56e0\u679c\u4e0e\u590d\u6742\u7cfb\u7edf\uff08Causality and Complex Systems\uff09<\/span><\/p>\n

\u5f81\u7a3f\u622a\u6b62\u65e5\u671f\uff1a2024\u5e749\u670824\u65e5<\/span><\/p>\n


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

\u901a\u8fc7\u4ee5\u4e0b\u94fe\u63a5\u8fdb\u5165\u5b98\u7f51\u67e5\u770b\u66f4\u591a\u4fe1\u606f\uff1ahttps:\/\/www.mdpi.com\/journal\/entropy\/special_issues\/causality_complex_systems<\/span><\/p>\n<\/section>\n<\/section>\n<\/section>\n<\/section>\n


<\/p>\n

\n

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

\u63a8\u8350\u9605\u8bfb<\/span><\/strong><\/strong><\/p>\n

1. <\/strong>\u56e0\u679c\u8868\u5f81\u5b66\u4e60\u6700\u65b0\u7efc\u8ff0\uff1a\u8fde\u63a5\u56e0\u679c\u79d1\u5b66\u548c\u673a\u5668\u5b66\u4e60\u7684\u6865\u6881<\/a><\/strong><\/span><\/strong><\/section>\n
2.<\/strong> \u9762\u5411\u56e0\u679c\u89c4\u5f8b\u7684\u8868\u793a\u5b66\u4e60\u65b0\u65b9\u6cd5\u2014\u2014\u56e0\u679c\u8868\u5f81\u5b66\u4e60\u6700\u65b0\u653b\u7565<\/a><\/strong><\/span><\/section>\n
3. <\/strong>\u56fe\u5f62\u7684\u903b\u8f91\u529b\u91cf\uff1a\u56e0\u679c\u56fe\u7684\u6982\u5ff5\u53ca\u5176\u5e94\u7528<\/a><\/strong><\/span><\/strong><\/section>\n
4. <\/strong><\/span>\u5f20\u6c5f\uff1a\u7b2c\u4e09\u4ee3\u4eba\u5de5\u667a\u80fd\u6280\u672f\u57fa\u7840\u2014\u2014\u4ece\u53ef\u5fae\u5206\u7f16\u7a0b\u5230\u56e0\u679c\u63a8\u7406 | \u96c6\u667a\u5b66\u56ed\u5168\u65b0\u8bfe\u7a0b<\/a><\/strong><\/strong><\/span><\/section>\n
<\/strong><\/strong>5.<\/strong> \u9f99\u5e74\u5927\u8fd0\u8d77\uff0c\u5b66\u4e60\u6b63\u5f53\u65f6\uff01\u89e3\u9501\u96c6\u667a\u5168\u7ad9\u5185\u5bb9\uff0c\u5f00\u542f\u65b0\u5e74\u5b66\u4e60\u8ba1\u5212<\/a><\/strong><\/strong><\/strong><\/strong><\/span><\/section>\n
6. <\/strong>\u52a0\u5165\u96c6\u667a\uff0c\u4e00\u8d77\u590d\u6742\uff01<\/strong><\/span><\/a><\/section>\n


<\/p>\n


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

\u70b9\u51fb\u201c\u9605\u8bfb\u539f\u6587\u201d\uff0c\u62a5\u540d\u8bfb\u4e66\u4f1a <\/strong><\/span><\/strong><\/span><\/strong><\/section>\n

<\/mp-style-type><\/p>\n<\/div>\n","protected":false},"excerpt":{"rendered":"

\u5bfc\u8bed \u56e0\u679c\u63a8\u65ad\u65e8\u5728\u63cf\u8ff0\u7ed9\u5b9a\u53d8\u91cf\u4e4b\u95f4\u7684\u56e0\u679c\u5173\u7cfb\u3002\u7136\u800c\uff0c\u5728\u8bb8\u591a\u5b9e\u9645\u7cfb\u7edf\u4e2d\uff0c\u53d8\u91cf\u901a\u5e38\u53ea\u80fd\u90e8\u5206\u89c2\u6d4b\u5230\uff0c\u800c\u4e00\u4e9b\u672a\u89c2\u6d4b\u5230\u7684\u53d8\u91cf\u53ef\u80fd\u643a\u5e26\u91cd\u8981\u4fe1\u606f\u5e76\u5bf9\u76ee\u6807\u4ea7\u751f\u56e0\u679c\u6548\u5e94\u3002\u8bc6\u522b\u8fd9\u4e9b\u672a\u89c2\u6d4b\u5230\u7684\u539f\u56e0\u4ecd\u7136\u662f\u4e00\u4e2a\u6311\u6218\u3002\u6700\u8fd1\u8fd9\u7bc7\u53d1\u8868\u4e8e Entropy \u300c\u56e0\u679c\u4e0e\u590d\u6742\u7cfb\u7edf\u7279\u520a\u300d\u7684\u6700\u65b0\u7814\u7a76\u4f7f\u7528\u4e00\u4e2a\u540d\u4e3a\u795e\u7ecf\u56e0\u679c\u4fe1\u606f\u63d0\u53d6\u5668\uff08Neural …<\/p>\n","protected":false},"author":0,"featured_media":48856,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":[],"categories":[1],"tags":[],"special":[],"_links":{"self":[{"href":"https:\/\/swarma.org\/index.php?rest_route=\/wp\/v2\/posts\/48863"}],"collection":[{"href":"https:\/\/swarma.org\/index.php?rest_route=\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/swarma.org\/index.php?rest_route=\/wp\/v2\/types\/post"}],"replies":[{"embeddable":true,"href":"https:\/\/swarma.org\/index.php?rest_route=%2Fwp%2Fv2%2Fcomments&post=48863"}],"version-history":[{"count":0,"href":"https:\/\/swarma.org\/index.php?rest_route=\/wp\/v2\/posts\/48863\/revisions"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/swarma.org\/index.php?rest_route=\/wp\/v2\/media\/48856"}],"wp:attachment":[{"href":"https:\/\/swarma.org\/index.php?rest_route=%2Fwp%2Fv2%2Fmedia&parent=48863"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/swarma.org\/index.php?rest_route=%2Fwp%2Fv2%2Fcategories&post=48863"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/swarma.org\/index.php?rest_route=%2Fwp%2Fv2%2Ftags&post=48863"},{"taxonomy":"special","embeddable":true,"href":"https:\/\/swarma.org\/index.php?rest_route=%2Fwp%2Fv2%2Fspecial&post=48863"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}