{"id":42460,"date":"2023-05-12T19:50:02","date_gmt":"2023-05-12T11:50:02","guid":{"rendered":"https:\/\/swarma.org\/?p=42460"},"modified":"2023-05-12T19:50:02","modified_gmt":"2023-05-12T11:50:02","slug":"%e7%89%a9%e7%90%86%e5%90%af%e5%8f%91%e7%9a%84%e6%b7%b1%e5%ba%a6%e7%94%9f%e6%88%90%e6%a8%a1%e5%9e%8b%ef%bc%9a%e6%a8%a1%e6%8b%9f%e8%87%aa%e7%84%b6%ef%bc%8c%e5%88%9b%e9%80%a0%e6%9c%aa%e6%9d%a5%e4%b8%a8","status":"publish","type":"post","link":"https:\/\/swarma.org\/?p=42460","title":{"rendered":"\u7269\u7406\u542f\u53d1\u7684\u6df1\u5ea6\u751f\u6210\u6a21\u578b\uff1a\u6a21\u62df\u81ea\u7136\uff0c\u521b\u9020\u672a\u6765\u4e28\u5468\u65e5\u76f4\u64ad\u00b7 AI+Science \u8bfb\u4e66\u4f1a"},"content":{"rendered":"
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(1) \u751f\u6210\u6a21\u578b\u6982\u8ff0<\/span><\/p>\n

a. \u7269\u7406\u542f\u53d1\u7684\u751f\u6210\u6a21\u578b\u5728\u5982\u4eca\u7684\u65e5\u5e38\u751f\u6d3b\u4e0e\u79d1\u5b66\u63a2\u7d22\u4e2d\u7684\u5e94\u7528<\/span><\/section>\n
b. \u4eceNormalizing flow model\u5230\u7531\u70ed\u529b\u5b66\u542f\u53d1\u7684\u6269\u6563\u6a21\u578b\u7684\u6f14\u5316<\/span><\/section>\n

(2) \u6cca\u677e\u6d41\u6a21\u578b(PFGM)<\/span><\/p>\n

a.PFGM\u5982\u4f55\u7528\u9759\u7535\u5b66\u7684\u7406\u8bba\u6765\u6784\u5efa\u751f\u6210\u6a21\u578b<\/span><\/section>\n
b. PFGM\u7684\u5177\u4f53\u8bad\u7ec3\u4e0e\u91c7\u6837\u7b97\u6cd5<\/span><\/section>\n
c. \u8ba8\u8bba\u6cca\u677e\u6bd4\u8d77\u4e4b\u524d\u5df2\u6709\u6a21\u578b\uff08\u5982diffusion model\uff09\u7684\u597d\u5904<\/span><\/section>\n

(3) \u5bf9\u6269\u5c55\u6cca\u677e\u6d41\u6a21\u578b (PFGM++)\u7684\u4ecb\u7ecd<\/span><\/p>\n

a. PFGM++\u5982\u4f55\u901a\u8fc7\u53d8\u5316\u589e\u5e7f\u7a7a\u95f4\u7684\u7ef4\u5ea6\u6765\u7edf\u4e00PFGM\u4e0ediffusion model<\/span><\/section>\n
b. PFGM++\u63ed\u793a\u4e86PFGM\u548cdiffusion model\u5404\u81ea\u7684\u4f18\u52a3<\/span><\/section>\n
c. \u5982\u4f55\u6839\u636e\u5177\u4f53\u7684\u4efb\u52a1\u6765\u9009\u62e9\u5408\u9002\u7684\u751f\u6210\u6a21\u578b<\/span><\/section>\n

(4) \u7269\u7406\u8fc7\u7a0b\u80fd\u5426\u63d0\u4f9b\u7ed9\u6211\u4eec\u66f4\u591a\u65b0\u7684\u751f\u6210\u6a21\u578b\uff1f<\/span><\/p>\n


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\u751f\u6210\u6a21\u578b<\/span><\/section>\n
\u6269\u6563\u6a21\u578b\uff08diffusion model\uff09<\/span><\/section>\n
\u6cca\u677e\u6d41\u6a21\u578b(PFGM)<\/span><\/section>\n
\u6269\u5c55\u6cca\u677e\u6d41\u6a21\u578b (PFGM++)<\/span><\/section>\n

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\u8bb8\u9038\u4f26\u662f\u9ebb\u7701\u7406\u5de5\u5b66\u9662\uff08MIT\uff09\u7535\u5b50\u4e0e\u8ba1\u7b97\u673a\u79d1\u5b66\uff08EECS\uff09\u7cfb\u4e09\u5e74\u7ea7\u5728\u8bfb\u535a\u58eb\u751f\uff0c\u5e08\u4eceTommi Jaakkola\u6559\u6388\u3002\u4ed6\u672c\u79d1\u5c31\u8bfb\u4e8e\u5317\u4eac\u5927\u5b66\u7684\u56fe\u7075\u73ed\u3002\u8bb8\u9038\u4f26\u7684\u7814\u7a76\u65b9\u5411\u4e3a\u673a\u5668\u5b66\u4e60\uff0c\u76ee\u524d\u4e3b\u8981\u5173\u6ce8\u66f4\u9ad8\u6548\u3001\u66f4\u53ef\u63a7\u7684\u751f\u6210\u6a21\u578b\u3002\u4ed6\u5728\u56fd\u9645\u4eba\u5de5\u667a\u80fd\u9876\u7ea7\u4f1a\u8bae\uff08\u5982ICML\u3001NeurIPS\u548cICLR\u7b49\uff09\u4e0a\u53d1\u8868\u4e86\u5341\u4f59\u7bc7\u6587\u7ae0\uff0c\u5e76\u591a\u6b21\u83b7\u5f97\u53e3\u5934\u62a5\u544a\u7684\u673a\u4f1a\u3002\u4e2a\u4eba\u4e3b\u9875\uff1a<\/span>https:\/\/yilun-xu.com<\/section>\n

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2023\u5e74<\/span>5\u670814\u65e5\uff08\u5468\u65e5\uff09  \u65e9\u666810:00-12:00<\/h3>\n

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

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\u751f\u6210\u6a21\u578b\u6982\u89c8 (swarma.org)\uff1ahttps:\/\/campus.swarma.org\/course\/5089<\/span><\/p>\n

\u5173\u4e8e\u6269\u6563\u6a21\u578b\u7684\u5b66\u4e60\u8def\u5f84<\/span><\/strong><\/span><\/section>\n

https:\/\/calvinyluo.com\/2022\/08\/26\/diffusion-tutorial.html<\/span><\/p>\n


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Song, Y., & Ermon, S. (2019). \u201cGenerative Modeling by Estimating Gradients of the Data Distribution.\u201d Neural Information Processing Systems\u201c<\/span><\/p>\n

\u63a8\u8350\u8bed\uff1a\u4f30\u8ba1\u6570\u636e\u5206\u5e03\u68af\u5ea6\uff1a\u5982\u4f55\u514b\u670d\u73b0\u6709\u751f\u6210\u5f0f\u6a21\u578b\u7684\u7f3a\u9677<\/span><\/p>\n

Ho, J. C., Jain, A et al. (2020b). \u201cDenoising Diffusion Probabilistic Models.\u201d ArXiv<\/span><\/p>\n

\u63a8\u8350\u8bed\uff1aAI\u7ed8\u753b\u7684\u57fa\u77f3: DDPM(Denoising Diffusion Probabilistic Model)<\/span><\/p>\n

Song, Y., Sohl-Dickstein, J., Kingma et al. (2021). \u201cScore-Based Generative Modeling through Stochastic Differential Equations.\u201d International Conference on Learning Representations(ICLR)<\/span><\/p>\n

\u63a8\u8350\u8bed\uff1a\u672c\u7814\u7a76\u6784\u5efa\u4e86\u4e00\u4e2a\u76f8\u5f53\u4e00\u822c\u5316\u7684\u751f\u6210\u6269\u6563\u6a21\u578b\u7406\u8bba\u6846\u67b6\uff0c\u5c06 DDPM\u3001SDE\u3001ODE \u7b49\u8bf8\u591a\u7ed3\u679c\u8054\u7cfb\u4e86\u8d77\u6765\u3002<\/span><\/p>\n

Karras, T., Aittala et al.(2022). \u201cElucidating the Design Space of Diffusion-Based Generative Models.\u201d ArXiv .<\/span><\/p>\n

\u63a8\u8350\u8bed\uff1a\u8fd9\u7bc7\u8bba\u6587\u5c06\u5148\u524d\u7684\u7814\u7a76\u7ec4\u7ec7\u6210\u4e00\u4e2a\u8fde\u8d2f\u7684\u5171\u540c\u6846\u67b6\uff0c\u4ee5\u4fc3\u6210\u65b0\u7684\u5efa\u6a21\u6539\u8fdb\u3002\u5bf9\u57fa\u4e8e\u6269\u6563\u8fc7\u7a0b\u7684\u6a21\u578b\u7684\u7406\u89e3\u548c\u5b9e\u73b0\u505a\u51fa\u4e86\u91cd\u8981\u8d21\u732e\u3002<\/span><\/p>\n

Xu, Y., Liu Z. et al (2023). \u201cPoisson Flow Generative Models \u201d Neural Information Processing Systems (NeurIPS)<\/span><\/p>\n

\u63a8\u8350\u8bed\uff1a\u8fd9\u7bc7\u8bba\u6587\u63d0\u51fa\u4e86\u4e00\u4e2a\u7531\u9759\u7535\u529b\u5b66\u542f\u53d1\u7684\u751f\u6210\u6a21\u578bPFGM\u3002\u8be5\u6a21\u578b\u6bd4\u6269\u6563\u6a21\u578b\u66f4\u4e3a\u9c81\u68d2\uff1b\u4e14\u5728\u6709\u6269\u6563\u6a21\u578b\u76f8\u540c\u6216\u8005\u66f4\u4f18\u7684\u751f\u6210\u8d28\u91cf\u60c5\u51b5\u4e0b\uff0c\u751f\u6210\u901f\u5ea6\u66f4\u5feb<\/span><\/p>\n

Xu, Y., Liu Z. et al (2023). \u201cPFGM++: Unlocking the Potential of Physics-Inspired Generative Models\u201d International Conference on Machine Learning (ICML)<\/span><\/p>\n

\u63a8\u8350\u8bed\uff1a\u8fd9\u7bc7\u8bba\u6587\u7edf\u4e00\u4e86\u73b0\u6709\u7684\u4e24\u79cd\u6700\u4f18\u7684\u751f\u6210\u6a21\u578b: \u6269\u6563\u6a21\u578b\u4e0ePFGM; \u8be5\u6587\u7ae0\u8ba8\u8bba\u4e86\u4ed6\u4eec\u7684\u4f18\u52a3\uff1b\u5e76\u4e14\u63d0\u51fa\u5982\u4f55\u627e\u5230\u4e00\u4e2a\u540c\u65f6\u5177\u6709\u4ed6\u4eec\u5404\u81ea\u4f18\u70b9\u7684\u65b0\u7684\u751f\u6210\u6a21\u578b\u3002<\/span><\/p>\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\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\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\u8bfb\u4e66\u4f1a\u4ece2023\u5e743\u670826\u65e5\u5f00\u59cb\uff0c\u6bcf\u5468\u65e5\u65e9\u4e0a 10:00-12:00 \u7ebf\u4e0a\u4e3e\u884c\uff0c\u6301\u7eed\u65f6\u95f4\u9884\u8ba110\u5468\u3002\u6b22\u8fce\u5bf9\u63a2\u7d22\u8fd9\u4e2a\u6fc0\u52a8\u4eba\u5fc3\u7684\u524d\u6cbf\u9886\u57df\u6709\u5174\u8da3\u7684\u670b\u53cb\u62a5\u540d\u53c2\u4e0e\u3002<\/span><\/section>\n

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\u4eba\u5de5\u667a\u80fd\u548c\u79d1\u5b66\u53d1\u73b0\u76f8\u4e92\u8d4b\u80fd\u7684\u65b0\u8303\u5f0f\uff1aAI+Science \u8bfb\u4e66\u4f1a\u542f\u52a8<\/a>
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\u70b9\u51fb\u201c\u9605\u8bfb\u539f\u6587\u201d\uff0c\u62a5\u540d\u8bfb\u4e66\u4f1a<\/span><\/p>\n

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