{"id":50117,"date":"2024-05-03T14:26:04","date_gmt":"2024-05-03T06:26:04","guid":{"rendered":"https:\/\/swarma.org\/?p=50117"},"modified":"2024-05-03T14:26:04","modified_gmt":"2024-05-03T06:26:04","slug":"yes-we-kan-mlp-out%ef%bc%81%e4%b8%80%e4%bd%9c%e5%88%98%e5%ad%90%e9%b8%a3%e7%9b%b4%e6%92%ad%e8%a7%a3%e8%af%bb%e5%85%a8%e6%96%b0%e7%a5%9e%e7%bb%8f%e7%bd%91%e7%bb%9c%e6%a1%86%e6%9e%b6kan","status":"publish","type":"post","link":"https:\/\/swarma.org\/?p=50117","title":{"rendered":"Yes, We KAN! MLP out\uff01\u4e00\u4f5c\u5218\u5b50\u9e23\u76f4\u64ad\u89e3\u8bfb\u5168\u65b0\u795e\u7ecf\u7f51\u7edc\u6846\u67b6KAN"},"content":{"rendered":"
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MIT\u5728\u8bfb\u535a\u58eb\u751f\u3001\u96c6\u667a\u4ff1\u4e50\u90e8AI+Science\u8bfb\u4e66\u4f1a<\/a>\u53d1\u8d77\u4eba\u4e4b\u4e00\u5218\u5b50\u9e23\uff0c\u6700\u8fd1\u4f5c\u4e3a\u7b2c\u4e00\u4f5c\u8005\u5171\u540c\u63d0\u51fa\u4e86\u2014\u2014KAN\uff08Kolmogorov-Arnold Networks\uff09\u6846\u67b6\u3002\u8fd9\u9879\u5de5\u4f5c\u98a0\u8986\u4e86\u673a\u5668\u5b66\u4e60\u4f20\u7edf\u7684\u591a\u5c42\u611f\u77e5\u673a\uff08MLP\uff09\u67b6\u6784\uff0c\u4e0d\u4ec5\u5728\u7406\u8bba\u4e0a\u62d3\u5c55\u4e86\u6df1\u5ea6\u5b66\u4e60\u6a21\u578b\u7684\u8fb9\u754c\uff0c\u66f4\u5728\u5b9e\u9645\u5e94\u7528\u4e2d\u5c55\u73b0\u51fa\u4e86\u5353\u8d8a\u7684\u6027\u80fd\u548c\u89e3\u91ca\u6027\u3002<\/span><\/strong><\/section>\n

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\u8bba\u6587\u901f\u9012\uff1aYes, We KAN!<\/strong><\/span><\/strong><\/strong><\/p>\n<\/section>\n

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\u8bba\u6587\u9898\u76ee\uff1aKAN: Kolmogorov\u2013Arnold Networks<\/span><\/p>\n

\u8bba\u6587\u5730\u5740\uff1ahttps:\/\/arxiv.org\/html\/2404.19756v1<\/span><\/p>\n<\/section>\n<\/section>\n<\/blockquote>\n


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1900\u5e74\uff0c\u5728\u56fd\u9645\u6570\u5b66\u5bb6\u5927\u4f1a\u7684\u5df4\u9ece\u6f14\u8bb2\u4e2d\uff0c\u5e0c\u5c14\u4f2f\u7279<\/span>\uff08David Hilbert\uff09<\/span>\u66fe\u63d0\u51fa\u4e8623\u4e2a\u5bf9\u6570\u5b66\u53d1\u5c55\u81f3\u5173\u91cd\u8981\u7684\u95ee\u9898\u3002Kolmogorov-Arnold\u8868\u793a\u5b9a\u7406\u6b63\u4e0e\u5176\u4e2d\u7684\u5e0c\u5c14\u4f2f\u7279\u7b2c13\u95ee\u9898\u5bc6\u5207\u76f8\u5173\u3002\u8be5\u5b9a\u7406\u6307\u51fa\uff0c\u5982\u679cf\u662f\u4efb\u610f\u4e00\u4e2a\u5b9a\u4e49\u5728\u6709\u754c\u57df\u4e0a\u7684\u591a\u53d8\u91cf\u8fde\u7eed\u51fd\u6570\uff0c\u5219\u8be5\u51fd\u6570\u53ef\u4ee5\u8868\u793a\u4e3a\u6709\u9650\u6570\u91cf\u7684\u5355\u53d8\u91cf\u3001\u8fde\u7eed\u51fd\u6570\u7684\u4e24\u5c42\u5d4c\u5957\u53e0\u52a0\u7684\u5f62\u5f0f\u3002<\/span><\/p>\n


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\u4e00\u4f5c\u76f4\u64ad\u89e3\u8bfb\uff1a<\/strong><\/span><\/strong><\/strong><\/p>\n

KAN: Kolmogorov-Arnold Networks<\/strong><\/span><\/strong><\/strong><\/p>\n<\/section>\n

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\u4e3b\u8bb2\u4eba\u7b80\u4ecb\uff1a<\/span><\/strong><\/span><\/h3>\n
<\/section>\n
\u5218\u5b50\u9e23<\/span><\/strong>\uff0c\u9ebb\u7701\u7406\u5de5\u5b66\u9662\uff08MIT\uff09\u7269\u7406\u7cfb\u535a\u58eb\u751f\uff0c\u5bfc\u5e08\u662f Max Tegmark\u30022020\u5e74\u4ece\u5317\u4eac\u5927\u5b66\u83b7\u5f97\u7269\u7406\u5b66\u58eb\u5b66\u4f4d\u3002\u4ed6\u7684\u7814\u7a76\u5174\u8da3\u5728AI\u548c\u7269\u7406\u7684\u4ea4\u53c9\uff1a\u4e00\u65b9\u9762AI for Physics\uff0c\u5229\u7528AI\u5de5\u5177\u81ea\u52a8\u5316\u7269\u7406\u89c4\u5f8b\u548c\u6982\u5ff5\u7684\u53d1\u73b0\uff1b\u53e6\u4e00\u65b9\u9762Physics for AI\uff0c\u5229\u7528\u7269\u7406\u542f\u53d1\u6784\u5efaAI\u7406\u8bba\u548c\u66f4\u5177\u53ef\u89e3\u91ca\u6027\u7684\u6a21\u578b\u3002\u4e2a\u4eba\u4e3b\u9875\uff1ahttps:\/\/kindxiaoming.github.io\/<\/span><\/section>\n

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\u5206\u4eab\u5927\u7eb2\uff1a<\/span><\/strong><\/span><\/h3>\n
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      \u8bba\u6587\u4e00\u4f5c\u89e3\u8bfb<\/strong>\uff1a\u5218\u5b50\u9e23\u535a\u58eb\u5c06\u76f4\u63a5\u6839\u636e\u8bba\u6587\u539f\u6587\uff0c\u9010\u7ae0\u6df1\u5165\u8bb2\u89e3KAN\u7684\u7406\u8bba\u57fa\u7840\u3001\u6a21\u578b\u67b6\u6784\u548c\u5b9e\u9a8c\u7ed3\u679c\u3002<\/span><\/section>\n<\/li>\n
    2. \n
      \u80cc\u540e\u7684\u601d\u8003\u903b\u8f91\u548c\u60f3\u6cd5<\/strong>\uff1a\u5206\u4eabKAN\u6a21\u578b\u7684\u7075\u611f\u6765\u6e90\uff0c\u4ee5\u53ca\u5982\u4f55\u4eceKolmogorov-Arnold\u8868\u793a\u5b9a\u7406\u4e2d\u6c72\u53d6\u601d\u60f3\uff0c\u6784\u5efa\u51fa\u5177\u6709\u5f3a\u5927\u8868\u8fbe\u80fd\u529b\u548c\u89e3\u91ca\u6027\u7684\u795e\u7ecf\u7f51\u7edc\u3002<\/span><\/section>\n<\/li>\n<\/ol>\n
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        \u63a2\u8ba8KAN\u6a21\u578b\u5728\u6570\u636e\u62df\u5408\u3001\u504f\u5fae\u5206\u65b9\u7a0b\u6c42\u89e3\u7b49\u9886\u57df\u7684\u5e94\u7528\u6f5c\u529b\u3002<\/span><\/section>\n<\/li>\n
      2. \n
        \u8ba8\u8bbaKAN\u6a21\u578b\u5bf9\u672a\u6765\u6df1\u5ea6\u5b66\u4e60\u6a21\u578b\u53d1\u5c55\u7684\u53ef\u80fd\u5f71\u54cd\uff0c\u4ee5\u53ca\u5b83\u5728AI+Science\u9886\u57df\u7684\u5e7f\u9614\u524d\u666f\u3002<\/span><\/section>\n<\/li>\n<\/ol>\n<\/ol>\n

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        \u53c2\u4e0e\u65b9\u5f0f\uff1a<\/span><\/strong><\/span><\/h2>\n

        \u76f4\u64ad<\/span><\/strong>\u65f6\u95f4<\/span><\/strong>\uff1a<\/span><\/h3>\n
        <\/span><\/section>\n
        2024\u5e745\u670811\u65e5\u665a\u4e0a8:00-10:00\u3002<\/span><\/section>\n
        <\/mp-common-videosnap><\/section>\n
        \u53c2\u4e0e\u65b9\u5f0f\uff1a<\/span><\/strong><\/span><\/section>\n
        <\/section>\n
        \u626b\u7801\u53c2\u4e0eAI+Science\u8bfb\u4e66\u4f1a<\/a>\uff0c\u52a0\u5165\u7fa4\u804a\uff0c\u83b7\u53d6\u7cfb\u5217\u8bfb\u4e66\u4f1a\u56de\u770b\u6743\u9650\uff0c\u6210\u4e3a\u79cd\u5b50\u7528\u6237\uff0c\u4e0e\u793e\u533a\u7684\u4e00\u7ebf\u79d1\u7814\u5de5\u4f5c\u8005\u4e0e\u4f01\u4e1a\u5b9e\u8df5\u8005\u6c9f\u901a\u4ea4\u6d41\uff0c\u5171\u540c\u63a8\u52a8\u591a\u667a\u80fd\u4f53\u8fd9\u4e00\u524d\u6cbf\u9886\u57df\u7684\u53d1\u5c55\u3002<\/span><\/section>\n

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

        \u53c2\u8003\u8d44\u6599<\/span><\/strong><\/span><\/h2>\n

        Ziming Liu, Yixuan Wang, Sachin Vaidya, et al. KAN: Kolmogorov-Arnold Networks<\/strong>. arXiv:2404.19756<\/em>, 2024<\/span><\/p>\n

        Paper: https:\/\/arxiv.org\/abs\/2404.19756<\/span><\/p>\n

        Github: https:\/\/github.com\/KindXiaoming\/pykan<\/span><\/p>\n

        Documentation: https:\/\/kindxiaoming.github.io\/pykan\/<\/span><\/p>\n

        \u6591\u56fe\u5730\u5740\uff1ahttps:\/\/pattern.swarma.org\/paper\/bfba8482-0849-11ef-8229-0242ac170005<\/span><\/section>\n


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        AI+Science \u8bfb\u4e66\u4f1a<\/strong><\/p>\n<\/section>\n<\/section>\n<\/section>\n<\/section>\n

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        AI+Science \u662f\u8fd1\u5e74\u5174\u8d77\u7684\u5c06\u4eba\u5de5\u667a\u80fd\u548c\u79d1\u5b66\u76f8\u7ed3\u5408\u7684\u4e00\u79cd\u8d8b\u52bf\u3002<\/span>\u4e00\u65b9\u9762\u662f AI for Science\uff0c\u673a\u5668\u5b66\u4e60\u548c\u5176\u4ed6 AI \u6280\u672f\u53ef\u4ee5\u7528\u6765\u89e3\u51b3\u79d1\u5b66\u7814\u7a76\u4e2d\u7684\u95ee\u9898\uff0c\u4ece\u9884\u6d4b\u5929\u6c14\u548c\u86cb\u767d\u8d28\u7ed3\u6784\uff0c\u5230\u6a21\u62df\u661f\u7cfb\u78b0\u649e\u3001\u8bbe\u8ba1\u4f18\u5316\u6838\u805a\u53d8\u53cd\u5e94\u5806\uff0c\u751a\u81f3\u50cf\u79d1\u5b66\u5bb6\u4e00\u6837\u8fdb\u884c\u79d1\u5b66\u53d1\u73b0\uff0c\u88ab\u79f0\u4e3a\u79d1\u5b66\u53d1\u73b0\u7684\u201c\u7b2c\u4e94\u8303\u5f0f\u201d\u3002<\/span>\u53e6\u4e00\u65b9\u9762\u662f Science for AI\uff0c\u79d1\u5b66\u5c24\u5176\u662f\u7269\u7406\u5b66\u4e2d\u7684\u89c4\u5f8b\u548c\u601d\u60f3\u542f\u53d1\u673a\u5668\u5b66\u4e60\u7406\u8bba\uff0c\u4e3a\u4eba\u5de5\u667a\u80fd\u7684\u53d1\u5c55\u63d0\u4f9b\u5168\u65b0\u7684\u89c6\u89d2\u548c\u65b9\u6cd5\u3002<\/span><\/section>\n
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        \u96c6\u667a\u4ff1\u4e50\u90e8\u8054\u5408\u65af\u5766\u798f\u5927\u5b66\u8ba1\u7b97\u673a\u79d1\u5b66\u7cfb\u535a\u58eb\u540e\u7814\u7a76\u5458\u5434\u6cf0\u9716\uff08Jure Leskovec \u6559\u6388\u6307\u5bfc\uff09\u3001\u54c8\u4f5b\u91cf\u5b50\u8ba1\u5212\u7814\u7a76\u5458\u6248\u9e3f\u4e1a\u3001\u9ebb\u7701\u7406\u5de5\u5b66\u9662\u7269\u7406\u7cfb\u535a\u58eb\u751f\u5218\u5b50\u9e23\uff08Max Tegmark \u6559\u6388\u6307\u5bfc\uff09\uff0c\u5171\u540c\u53d1\u8d77\u4ee5\u201cAI+Science<\/a>\u201d\u4e3a\u4e3b\u9898\u7684\u8bfb\u4e66\u4f1a\uff0c\u63a2\u8ba8\u8be5\u9886\u57df\u7684\u91cd\u8981\u95ee\u9898\uff0c\u5171\u5b66\u5171\u7814\u76f8\u5173\u6587\u732e\u3002<\/span><\/span>\u8bfb\u4e66\u4f1a\u5df2\u5b8c\u7ed3\uff0c\u73b0\u5728\u62a5\u540d\u53ef\u52a0\u5165\u793e\u7fa4\u5e76\u89e3\u9501<\/span>\u56de\u653e<\/span>\u89c6\u9891\u6743\u9650\u3002<\/span><\/span><\/span><\/section>\n
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        \u6570\u5341\u5e74\u6765\uff0c\u4eba\u5de5\u667a\u80fd\u7684\u7406\u8bba\u53d1\u5c55\u548c\u6280\u672f\u5b9e\u8df5\u4e00\u76f4\u4e0e\u79d1\u5b66\u63a2\u7d22\u76f8\u4f34\u800c\u751f\uff0c\u5c24\u5176\u5728\u4ee5\u5927\u6a21\u578b\u4e3a\u4ee3\u8868\u7684\u4eba\u5de5\u667a\u80fd\u6280\u672f\u5e94\u7528\u96c6\u4e2d\u7206\u53d1\u7684\u5f53\u4e0b\uff0c\u4eba\u5de5\u667a\u80fd\u6b63\u5728\u52a0\u901f\u7269\u7406\u3001\u5316\u5b66\u3001\u751f\u7269\u7b49\u57fa\u7840\u79d1\u5b66\u7684\u9769\u65b0\uff0c\u800c<\/span>\u8fd9\u4e9b\u5b66\u79d1\u4e5f\u5728\u53cd\u8fc7\u6765\u542f\u53d1\u4eba\u5de5\u667a\u80fd\u6280\u672f\u521b\u65b0\u3002\u5728\u6b64\u8fc7\u7a0b\u4e2d\uff0c\u6570\u5b66\u4f5c\u4e3a\u517c\u5177\u7406\u8bba\u5c5e\u6027\u4e0e\u5de5\u5177\u5c5e\u6027\u7684\u91cd\u8981\u57fa\u7840\u5b66\u79d1\uff0c\u4e0e\u4eba\u5de5\u667a\u80fd\u5173\u7cfb\u751a\u5bc6\uff0c\u76f8\u8f85\u76f8\u6210\u3002\u4e00\u65b9\u9762\uff0c\u4eba\u5de5\u667a\u80fd\u5728\u89e3\u51b3<\/span>\u6570\u5b66\u9886\u57df\u7684\u8bf8\u591a\u5de5\u7a0b\u95ee\u9898\u3001\u7406\u8bba\u95ee\u9898\u4e43\u81f3\u5723\u676f\u96be\u9898\u4e0a\u5c61\u521b\u8bb0\u5f55\u3002\u53e6\u4e00\u65b9<\/span>\u9762\uff0c\u6570\u5b66\u6301\u7eed\u4e3a\u4eba\u5de5\u667a\u80fd\u6784\u7b51\u7406\u8bba\u57fa\u77f3\u5e76\u62d3\u5c55\u5176\u672a\u6765\u7a7a\u95f4\u3002\u8fd9\u4e24\u4e2a\u5173\u952e\u9886\u57df\u7684\u4ea4\u53c9\u878d\u5408\uff0c\u6b63\u5728\u63ed\u5f00\u4e0b\u4e2a\u65f6\u4ee3\u7684\u79d1\u5b66\u4e4b\u5e55\u3002<\/span><\/span><\/p>\n


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

        \u4e3a\u4e86\u63a2\u7d22\u6570\u5b66\u4e0e\u4eba\u5de5\u667a\u80fd\u6df1\u5ea6\u878d\u5408\u7684\u53ef\u80fd\u6027\uff0c\u96c6\u667a\u4ff1\u4e50\u90e8\u8054\u5408\u540c\u6d4e\u5927\u5b66\u7279\u8058\u7814\u7a76\u5458\u9648\u5c0f\u6768\u3001\u6e05\u534e\u5927\u5b66\u4ea4\u53c9\u4fe1\u606f\u5b66\u9662\u52a9\u7406\u6559\u6388\u8881\u6d0b\u3001\u5357\u6d0b\u7406\u5de5\u5927\u5b66\u526f\u6559\u6388\u590f\u514b\u6797\u4e09\u4f4d\u8001\u5e08\uff0c\u5171\u540c\u53d1\u8d77\u201c\u4eba\u5de5\u667a\u80fd\u4e0e\u6570\u5b66\u201d\u8bfb\u4e66\u4f1a\uff0c\u5e0c\u671b\u4ece AI\u3000for\u3000Math\uff0cMath\u3000for\u3000AI \u4e24\u4e2a\u65b9\u9762\u6df1\u5165\u63a2\u8ba8\u4eba\u5de5\u667a\u80fd\u4e0e\u6570\u5b66\u7684\u5bc6\u5207\u8054\u7cfb\u3002<\/span>\u8bfb\u4e66\u4f1a\u5df2\u5b8c\u7ed3\uff0c\u73b0\u5728\u62a5\u540d\u53ef\u52a0\u5165\u793e\u7fa4\u5e76\u89e3\u9501<\/span>\u56de\u653e<\/span>\u89c6\u9891\u6743\u9650\u3002<\/span><\/span><\/span><\/p>\n


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

        <\/section>\n

        \u8be6\u60c5\u8bf7\u89c1\uff1a<\/span><\/span><\/p>\n

        \u4eba\u5de5\u667a\u80fd\u4e0e\u6570\u5b66\u8bfb\u4e66\u4f1a\u542f\u52a8\uff1aAI for Math\uff0cMath for AI<\/a><\/span><\/p>\n

        \n


        <\/p>\n


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

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


        <\/p>\n

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