{"id":30403,"date":"2021-11-28T21:24:34","date_gmt":"2021-11-28T13:24:34","guid":{"rendered":"https:\/\/swarma.org\/?p=30403"},"modified":"2021-11-28T21:24:34","modified_gmt":"2021-11-28T13:24:34","slug":"nat-mach-intell%ef%bc%9a%e4%bc%98%e5%8c%96%e7%89%a9%e7%90%86%e5%ad%a6%e5%92%8c%e6%9c%ba%e5%99%a8%e5%ad%a6%e4%b9%a0%e4%b9%8b%e9%97%b4%e7%9a%84%e5%8d%8f%e5%90%8c%e4%bd%9c%e7%94%a8","status":"publish","type":"post","link":"https:\/\/swarma.org\/?p=30403","title":{"rendered":"Nat. Mach. Intell\uff1a\u4f18\u5316\u7269\u7406\u5b66\u548c\u673a\u5668\u5b66\u4e60\u4e4b\u95f4\u7684\u534f\u540c\u4f5c\u7528"},"content":{"rendered":"
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\u7269\u7406\u5b66\u53ef\u4ee5\u5e2e\u52a9\u6211\u4eec\u5bf9\u673a\u5668\u5b66\u4e60\u6709\u66f4\u6df1\u523b\u7684\u8ba4\u77e5\uff0c\u53cd\u8fc7\u6765\uff0c\u5148\u8fdb\u7684\u673a\u5668\u5b66\u4e60\u6a21\u578b\u5219\u53ef\u4ee5\u5e2e\u52a9\u89e3\u51b3\u7269\u7406\u79d1\u5b66\u4e2d\u6d89\u53ca\u5230\u5927\u91cf\u6570\u636e\u7684\u95ee\u9898\uff0c\u5982\u6d41\u4f53\u529b\u5b66\u3001\u9ad8\u80fd\u7269\u7406\u6216\u5929\u6c14\u9884\u62a5\u300211\u670816\u65e5\uff0cNature Machine Intelligence<\/em> \u64b0\u5199\u793e\u8bba\u6587\u7ae0\u300a\u4f18\u5316\u7269\u7406\u5b66\u548c\u673a\u5668\u5b66\u4e60\u4e4b\u95f4\u7684\u534f\u540c\u4f5c\u7528\u300b\uff0c\u5f3a\u8c03\u4e86\u7269\u7406\u5b66\u548c\u673a\u5668\u5b66\u4e60\u4e4b\u95f4\u5efa\u7acb\u65b0\u8054\u7cfb\u4f1a\u50ac\u751f\u5f3a\u5927\u7684\u7b97\u6cd5\u3002<\/strong><\/p>\n


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\u7814\u7a76\u9886\u57df\uff1a<\/strong><\/strong><\/span><\/strong><\/span><\/strong><\/span><\/strong>\u7269\u7406\u5b66\uff0c\u673a\u5668\u5b66\u4e60\uff0c\u795e\u7ecf\u7f51\u7edc<\/span><\/strong><\/span><\/p>\n<\/section>\n<\/section>\n<\/section>\n<\/section>\n<\/section>\n

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Nat. Mach. Intell.  | \u4f5c\u8005<\/strong><\/span><\/p>\n

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Optimizing the synergy between physics and machine learning<\/span><\/span><\/p>\n

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1. \u7269\u7406\u5b66\u589e\u8fdb\u5bf9\u673a\u5668\u5b66\u4e60\u7684\u8ba4\u77e5<\/strong><\/strong><\/p>\n<\/section>\n

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\u4ece\u53e6\u4e00\u4e2a\u89d2\u5ea6\u6765\u770b\uff0c\u7406\u8bba\u7269\u7406\u5b66\u6709\u671b\u5e2e\u52a9\u6211\u4eec\u83b7\u5f97\u5bf9\u673a\u5668\u5b66\u4e60\u7684\u672c\u8d28\u8ba4\u77e5<\/strong>\u30021984\u5e74 L. G. Valiant \u7684\u4e00\u7bc7\u7ecf\u5178\u8bba\u6587\u662f\u8be5\u9886\u57df\u7684\u5960\u57fa\u4e4b\u4f5c [1]\uff0c\u9610\u8ff0\u4e86\u5173\u4e8e\u5b66\u4e60\u7684\u4e25\u683c\u7edf\u8ba1\u7406\u8bba\u3002\u4f46\u968f\u77402010\u5e74\u4ee5\u6765\u6df1\u5ea6\u5b66\u4e60\u7684\u5174\u8d77\uff0c\u6df1\u5ea6\u795e\u7ecf\u7f51\u7edc\u4ee4\u4eba\u60ca\u8bb6\u7684\u3001\u4e0d\u5408\u7406\u7684\u826f\u597d\u6027\u80fd\u548c\u6cdb\u5316\u80fd\u529b\uff0c\u63d0\u51fa\u4e86\u8fdb\u4e00\u6b65\u7684\u95ee\u9898\u3002<\/span><\/p>\n


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\u5728 Nature Physics<\/em> \u6700\u8fd1\u7684\u4e00\u7bc7\u8bc4\u8bba\u6587\u7ae0\u4e2d [2]\uff0cLenka zdeborov\u00e1 \u547c\u5401\uff0c\u53ef\u4ee5\u5c1d\u8bd5\u7528\u7269\u7406\u5b66\u542f\u53d1\u7684\u65b9\u6cd5\u6765\u89e3\u51b3\u8fd9\u4e9b\u95ee\u9898\uff0c\u6307\u51fa\u57fa\u4e8e\u7269\u7406\u5b66\u5bb6\u7684\u7ecf\u9a8c\uff0c\u53ef\u901a\u8fc7\u5bfb\u627e\u80fd\u591f\u6293\u4f4f\u95ee\u9898\u672c\u8d28\u7684\u6a21\u578b\uff0c\u5ffd\u7565\u8bf8\u591a\u7ec6\u8282\uff0c\u5e76\u7528\u5206\u6790\u6027\u7814\u7a76\u6765\u68c0\u9a8c\u6a21\u578b\uff0c\u4ece\u800c\u5904\u7406\u5927\u91cf\u4e0d\u540c\u5b9e\u9a8c\u4ea7\u751f\u7684\u89c2\u5bdf\u7ed3\u679c\u3002<\/span><\/p>\n


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\u4e00\u4e2a\u5178\u578b\u7684\u4f8b\u5b50\u662f\u975e\u5e38\u6210\u529f\u7684\u78c1\u6027\u7684\u4f0a\u8f9b\u6a21\u578b<\/strong><\/a>\uff0c\u8fd9\u4e2a\u6a21\u578b\u4e0d\u5305\u542b\u4efb\u4f55\u78c1\u76f8\u4e92\u4f5c\u7528\u7684\u91cf\u5b50\u529b\u5b66\u7ec6\u8282\u6216\u6750\u6599\u6027\u8d28\uff0c\u4f46\u89e3\u91ca\u4e86\u8bb8\u591a\u4e0d\u540c\u7c7b\u578b\u7684\u5b9e\u9a8c\u73b0\u8c61\u3002\u4e8b\u5b9e\u4e0a\uff0c\u4f0a\u8f9b\u6a21\u578b\u5728\u673a\u5668\u5b66\u4e60\u4e2d\u4e5f\u88ab\u8bc1\u660e\u662f\u6709\u7528\u7684\uff0c\u56e0\u4e3a Hopfield \u7f51\u7edc\u53ef\u4ee5\u770b\u4f5c\u662f\u795e\u7ecf\u7f51\u7edc\u7684\u4f0a\u8f9b\u6a21\u578b\u3002\u8fd9\u65b9\u9762\u7684\u52aa\u529b\u53ef\u4ee5\u5e2e\u52a9\u5efa\u7acb\u5bf9\u6df1\u5ea6\u5b66\u4e60\u7684\u7406\u8bba\u7406\u89e3\uff0c\u8bf4\u660e\u4e3a\u4ec0\u4e48\u5b83\u8868\u73b0\u5f97\u8fd9\u4e48\u597d[3]\u3002<\/span><\/p>\n


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2. \u673a\u5668\u5b66\u4e60\u5e2e\u52a9\u89e3\u51b3\u7269\u7406\u95ee\u9898<\/strong><\/strong><\/p>\n<\/section>\n

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\u4ece\u5b9e\u9645\u5e94\u7528\u7684\u89d2\u5ea6\u6765\u770b\uff0c\u6709\u8bb8\u591a\u673a\u4f1a\u53ef\u4ee5\u5f88\u597d\u5730\u5229\u7528\u6700\u5148\u8fdb\u7684\u673a\u5668\u5b66\u4e60\u6a21\u578b\uff0c\u89e3\u51b3\u7269\u7406\u79d1\u5b66\u4e2d\u6d89\u53ca\u5230\u5927\u91cf\u6570\u636e\u7684\u95ee\u9898<\/strong>\uff0c\u5982\u6d41\u4f53\u529b\u5b66 [4]\u3001\u9ad8\u80fd\u7269\u7406 [5] \u6216\u5929\u6c14\u9884\u62a5 [6]\u3002\u4e00\u4e2a\u6d3b\u8dc3\u7684\u4e3b\u9898\u662f\uff0c\u4f7f\u7528\u673a\u5668\u5b66\u4e60\u6a21\u578b\uff0c\u4ee5\u504f\u5fae\u5206\u65b9\u7a0b\u7684\u5f62\u5f0f\u5b66\u4e60\u6570\u5b66\u6cd5\u5219\uff0c\u8fd9\u662f\u6e4d\u6d41\u4e4b\u7c7b\u7684\u590d\u6742\u52a8\u529b\u5b66\u73b0\u8c61\u7684\u57fa\u7840\u3002\u5728 Nature Reviews Physics<\/em> \u6700\u8fd1\u7684\u4e00\u7bc7\u7efc\u8ff0\u6587\u7ae0<\/a>\u4e2d [7]\uff0cGeorge Karniadakis \u548c\u540c\u4e8b\u4eec\u8ba8\u8bba\u4e86\u7269\u7406\u5b66\u53ef\u4ee5\u5d4c\u5165\u5230\u8fd9\u4e9b\u65b9\u6cd5\u4e2d\u7684\u5404\u79cd\u65b9\u5f0f\uff0c\u4ee5\u89e3\u51b3\u590d\u6742\u7684\u52a8\u529b\u5b66\u95ee\u9898\uff0c\u4ece\u5730\u9707\u9884\u6d4b\u5230\u5206\u5b50\u52a8\u529b\u5b66\u3002<\/span><\/p>\n


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\u53e6\u4e00\u4e2a\u5f88\u6709\u524d\u666f\u7684\u8054\u7cfb\uff0c\u662f\u901a\u8fc7\u6df1\u5ea6\u5b66\u4e60\u6765\u89e3\u51b3\u4f18\u5316\u95ee\u9898\uff0c\u7279\u522b\u662f\u7ec4\u5408\u4f18\u5316\u95ee\u9898<\/strong>\u3002\u5728\u8fd9\u4e9b\u95ee\u9898\u4e2d\uff0c\u6700\u4f18\u89e3\u5fc5\u987b\u5728\u4e00\u4e2a\u975e\u5e38\u5927\u4f46\u6709\u9650\u7684\u53ef\u80fd\u6784\u578b\u7a7a\u95f4\u4e2d\u627e\u5230\uff0c\u8fd9\u4e2a\u7a7a\u95f4\u7684\u5927\u5c0f\u968f\u95ee\u9898\u7684\u8f93\u5165\u5927\u5c0f\u6210\u6307\u6570\u89c4\u6a21\u589e\u957f\uff0c\u4f7f\u5f97\u57fa\u4e8e\u7a77\u4e3e\u641c\u7d22\u7684\u7b56\u7565\u53d8\u5f97\u4e0d\u53ef\u884c\u3002\u4f17\u6240\u5468\u77e5\u7684\u4f8b\u5b50\u5305\u62ec\u89e3\u51b3\u9b54\u65b9\u3001\u65c5\u884c\u63a8\u9500\u5458\u95ee\u9898\uff0c\u6216\u8005\u627e\u5230\u86cb\u767d\u8d28\u7684 3D \u7ed3\u6784\u3002Mohammed Hibat-Allah \u7b49\u4eba\u5728 [8] \u4e2d\u63d0\u51fa\u4e86\u4e00\u79cd\u4f18\u5316\u7684\u65b0\u65b9\u6cd5\uff0c\u878d\u5408\u4e86\u7ecf\u5178\u7269\u7406\u5b66\u3001\u91cf\u5b50\u7269\u7406\u5b66\u4ee5\u53ca\u6df1\u5ea6\u5b66\u4e60\u7684\u6982\u5ff5\uff0c\u7279\u522b\u9002\u7528\u4e8e\u5bfb\u627e\u65e0\u5e8f\u4f0a\u8f9b\u7cfb\u7edf<\/span>\uff08disordered Ising systems\uff09<\/span>\u7684\u57fa\u6001\u3002<\/span><\/p>\n


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\u5728\u7edf\u8ba1\u7269\u7406\u5b66\u4e2d\uff0c\u4f18\u5316\u95ee\u9898\u53ef\u4ee5\u901a\u8fc7\u4e00\u79cd\u53eb\u505a\u6a21\u62df\u9000\u706b<\/strong><\/span>\uff08simulated annealing\uff09<\/span>\u7684\u8ba1\u7b97\u65b9\u6cd5\u6765\u89e3\u51b3\u3002\u8fd9\u662f\u4e00\u4e2a\u542f\u53d1\u5f0f\u7684\u8fc7\u7a0b\uff0c\u7075\u611f\u6765\u81ea\u4e8e\u51b6\u91d1\u4e2d\u7684\u9000\u706b\uff0c\u6750\u6599\u88ab\u8fc5\u901f\u52a0\u70ed\uff0c\u7136\u540e\u7f13\u6162\u51b7\u5374\uff0c\u4f7f\u5f97\u6750\u6599\u80fd\u591f\u5728\u5fae\u5c3a\u5ea6\u4e0a\u91cd\u65b0\u6392\u5217\u6210\u5177\u6709\u6240\u9700\u7279\u6027\u7684\u6700\u4f73\u7ed3\u6784\u3002\u6a21\u62df\u9000\u706b\u7b97\u6cd5\u901a\u8fc7\u9010\u6e10\u51cf\u5c11\u70ed\u6da8\u843d\uff0c\u6765\u63a2\u7d22\u4e00\u4e2a\u80fd\u91cf\u7a7a\u95f4<\/span>\uff08energy landscape\uff09<\/span>\uff0c\u4ee5\u627e\u5230\u5176\u5168\u5c40\u6700\u5c0f\u503c\u3002\u4f8b\u5982\u4e0b\u56fe\u662f\u4e00\u4e2a\u5177\u6709\u660e\u786e\u5168\u5c40\u6700\u5c0f\u503c\u7684\u7c97\u7cd9\u80fd\u91cf\u7a7a\u95f4\u7684\u4f8b\u5b50\u3002<\/span><\/p>\n


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\u5173\u4e8e\u86cb\u767d\u6298\u53e0\u7684\u7b80\u5316\u7684\u7c97\u7cd9\u80fd\u91cf\u56fe\u666f\u3002| Source: [9]. Credit: Springer Nature Ltd<\/span><\/p>\n


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\u65e0\u8bba\u662f\u7ecf\u5178\u7684\u8fd8\u662f\u91cf\u5b50\u7684\u6a21\u62df\u9000\u706b\uff0c\u5bf9\u4e8e\u4f18\u5316\u95ee\u9898\u90fd\u975e\u5e38\u6709\u7528\uff0c\u4f46\u662f\u901a\u8fc7\u201c\u964d\u6e29\u201d<\/span>\uff08\u51cf\u5c11\u70ed\u6da8\u843d\uff09<\/span>\u6765\u63a2\u7d22\u80fd\u91cf\u7a7a\u95f4\u901a\u5e38\u662f\u4e00\u4e2a\u7f13\u6162\u7684\u8fc7\u7a0b\u3002Hibat-Allah \u7b49\u4eba\u5c06\u6a21\u62df\u9000\u706b\u548c\u53d8\u5206\u65b9\u6cd5\u7ed3\u5408\u8d77\u6765\uff0c\u4f7f\u7528\u9012\u5f52\u795e\u7ecf\u7f51\u7edc\u53c2\u6570\u5316\u7cfb\u7edf\u72b6\u6001\u7684\u8054\u5408\u5206\u5e03\u3002\u8fd9\u79cd\u65b0\u65b9\u6cd5\u88ab\u79f0\u4e3a\u53d8\u5206\u795e\u7ecf\u9000\u706b<\/strong><\/span>\uff08Variational neural annealing\uff09<\/span>\uff0c\u5b83\u663e\u8457\u5730\u52a0\u5feb\u4e86\u6a21\u62df\u9000\u706b\u8fc7\u7a0b\u3002<\/span><\/p>\n


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1. L. G. Valiant. A theory of the learnable. Communications of the ACM. Volume 27 Issue 11. Nov. 1984 pp 1134\u20131142.https:\/\/dl.acm.org\/doi\/10.1145\/1968.1972<\/span><\/p>\n

2. Zdeborov\u00e1, L. Understanding deep learning is also a job for physicists. Nat. Phys. 16, 602\u2013604 (2020). https:\/\/doi.org\/10.1038\/s41567-020-0929-2<\/span><\/p>\n

3. Yasaman Bahri et al. Statistical Mechanics of Deep Learning. Annual Review of Condensed Matter Physics. Vol. 11:501-528 (Volume publication date March 2020) https:\/\/doi.org\/10.1146\/annurev-conmatphys-031119-050745<\/span><\/p>\n

4. Lagemann, C., Lagemann, K., Mukherjee, S. et al. Deep recurrent optical flow learning for particle image velocimetry data. Nat Mach Intell 3, 641\u2013651 (2021). https:\/\/doi.org\/10.1038\/s42256-021-00369-0. https:\/\/www.nature.com\/articles\/s42256-021-00369-0<\/span><\/p>\n

5. Dan Guest,  Kyle Cranmer,  Daniel Whiteson. Deep Learning and its Application to LHC Physics.  arXiv:1806.11484 [hep-ex] (2018).https:\/\/arxiv.org\/abs\/1806.11484<\/span><\/p>\n

6. Ravuri, S., Lenc, K., Willson, M. et al. Skilful precipitation nowcasting using deep generative models of radar. Nature 597, 672\u2013677 (2021). https:\/\/www.nature.com\/articles\/s41586-021-03854-z<\/span><\/p>\n

7. Karniadakis, G.E., Kevrekidis, I.G., Lu, L. et al. Physics-informed machine learning. Nat Rev Phys 3, 422\u2013440 (2021). https:\/\/www.nature.com\/articles\/s42254-021-00314-5<\/span><\/p>\n

8. Hibat-Allah, M., Inack, E.M., Wiersema, R. et al. Variational neural annealing. Nat Mach Intell 3, 952\u2013961 (2021). https:\/\/www.nature.com\/articles\/s42256-021-00401-3<\/span><\/p>\n

9. Kuhlman, B., Bradley, P. Advances in protein structure prediction and design. Nat Rev Mol Cell Biol 20, 681\u2013697 (2019). https:\/\/www.nature.com\/articles\/s41580-019-0163-x<\/span><\/p>\n

10. Biamonte, J., Wittek, P., Pancotti, N. et al. Quantum machine learning. Nature 549, 195\u2013202 (2017). https:\/\/www.nature.com\/articles\/nature23474\/<\/span><\/p>\n

11. Giuseppe Carleo et al. Machine learning and the physical sciences. Rev. Mod. Phys. 91, 045002 (2019). https:\/\/journals.aps.org\/rmp\/abstract\/10.1103\/RevModPhys.91.045002<\/span><\/p>\n

12. https:\/\/neurips.cc\/Conferences\/2021\/Schedule?showEvent=21862<\/span><\/p>\n


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