http://www.cslt.org/mediawiki/index.php?action=history&feed=atom&title=%E7%AC%AC%E4%B8%89%E5%8D%81%E4%B9%9D%E7%AB%A0_%E7%94%9F%E7%89%A9%E6%8B%9F%E6%80%81%E8%AF%81%E6%8D%AE 2026-04-06T08:34:41Z 本wiki的该页面的版本历史 MediaWiki 1.23.3 http://www.cslt.org/mediawiki/index.php?title=%E7%AC%AC%E4%B8%89%E5%8D%81%E4%B9%9D%E7%AB%A0_%E7%94%9F%E7%89%A9%E6%8B%9F%E6%80%81%E8%AF%81%E6%8D%AE&diff=39151&oldid=prev 2022-08-22T08:19:36Z

<p></p> <table class='diff diff-contentalign-left'> <col class='diff-marker' /> <col class='diff-content' /> <col class='diff-marker' /> <col class='diff-content' /> <tr style='vertical-align: top;'> <td colspan='2' style="background-color: white; color:black; text-align: center;">←上一版本</td> <td colspan='2' style="background-color: white; color:black; text-align: center;">2022年8月22日 (一) 08:19的版本</td> </tr><tr><td colspan="2" class="diff-lineno">第10行：</td> <td colspan="2" class="diff-lineno">第10行：</td></tr> <tr><td class='diff-marker'>&#160;</td><td style="background-color: #f9f9f9; color: #333333; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #e6e6e6; vertical-align: top; white-space: pre-wrap;"><div>* AI100问：机器学习如何发现生物拟态证据？[http://aigraph.cslt.org/ai100/AI-100-28-机器学习如何发现生物拟态证据.pdf]</div></td><td class='diff-marker'>&#160;</td><td style="background-color: #f9f9f9; color: #333333; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #e6e6e6; vertical-align: top; white-space: pre-wrap;"><div>* AI100问：机器学习如何发现生物拟态证据？[http://aigraph.cslt.org/ai100/AI-100-28-机器学习如何发现生物拟态证据.pdf]</div></td></tr> <tr><td class='diff-marker'>&#160;</td><td style="background-color: #f9f9f9; color: #333333; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #e6e6e6; vertical-align: top; white-space: pre-wrap;"><div>* 维基百科：生物拟态[http://aigraph.cslt.org/courses/39/拟态.pdf][http://aigraph.cslt.org/courses/39/Mimicry.pdf]</div></td><td class='diff-marker'>&#160;</td><td style="background-color: #f9f9f9; color: #333333; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #e6e6e6; vertical-align: top; white-space: pre-wrap;"><div>* 维基百科：生物拟态[http://aigraph.cslt.org/courses/39/拟态.pdf][http://aigraph.cslt.org/courses/39/Mimicry.pdf]</div></td></tr> <tr><td class='diff-marker'>−</td><td style="color:black; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #ffe49c; vertical-align: top; white-space: pre-wrap;"><div>&#160;</div></td><td class='diff-marker'>+</td><td style="color:black; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #a3d3ff; vertical-align: top; white-space: pre-wrap;"><div><ins class="diffchange diffchange-inline">* 维基百科：Müllerian 拟态 [http://aigraph.cslt.org/courses/39/Müllerian_mimicry.pdf]</ins></div></td></tr> <tr><td colspan="2">&#160;</td><td class='diff-marker'>+</td><td style="color:black; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #a3d3ff; vertical-align: top; white-space: pre-wrap;"><div><ins class="diffchange diffchange-inline">* 对比损失训练准则 [https://smilelingyong.github.io/2019/05/23/Contrastive-Loss-contrast-loss-function-and-gradient-calculation/]</ins></div></td></tr> <tr><td class='diff-marker'>&#160;</td><td style="background-color: #f9f9f9; color: #333333; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #e6e6e6; vertical-align: top; white-space: pre-wrap;"></td><td class='diff-marker'>&#160;</td><td style="background-color: #f9f9f9; color: #333333; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #e6e6e6; vertical-align: top; white-space: pre-wrap;"></td></tr> <tr><td class='diff-marker'>&#160;</td><td style="background-color: #f9f9f9; color: #333333; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #e6e6e6; vertical-align: top; white-space: pre-wrap;"><div>==视频展示==</div></td><td class='diff-marker'>&#160;</td><td style="background-color: #f9f9f9; color: #333333; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #e6e6e6; vertical-align: top; white-space: pre-wrap;"><div>==视频展示==</div></td></tr> <tr><td colspan="2" class="diff-lineno">第18行：</td> <td colspan="2" class="diff-lineno">第19行：</td></tr> <tr><td class='diff-marker'>&#160;</td><td style="background-color: #f9f9f9; color: #333333; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #e6e6e6; vertical-align: top; white-space: pre-wrap;"><div>* 会拟态的动物合集 [https://www.bilibili.com/video/BV1G5411t7DR?spm_id_from=333.337.search-card.all.click]</div></td><td class='diff-marker'>&#160;</td><td style="background-color: #f9f9f9; color: #333333; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #e6e6e6; vertical-align: top; white-space: pre-wrap;"><div>* 会拟态的动物合集 [https://www.bilibili.com/video/BV1G5411t7DR?spm_id_from=333.337.search-card.all.click]</div></td></tr> <tr><td class='diff-marker'>&#160;</td><td style="background-color: #f9f9f9; color: #333333; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #e6e6e6; vertical-align: top; white-space: pre-wrap;"><div>* 拟态专家大赏 [https://www.bilibili.com/video/BV1Zh411B7bu?spm_id_from=333.337.search-card.all.click]</div></td><td class='diff-marker'>&#160;</td><td style="background-color: #f9f9f9; color: #333333; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #e6e6e6; vertical-align: top; white-space: pre-wrap;"><div>* 拟态专家大赏 [https://www.bilibili.com/video/BV1Zh411B7bu?spm_id_from=333.337.search-card.all.click]</div></td></tr> <tr><td class='diff-marker'>−</td><td style="color:black; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #ffe49c; vertical-align: top; white-space: pre-wrap;"><div><del style="font-weight: bold; text-decoration: none;"></del></div></td><td colspan="2">&#160;</td></tr> <tr><td class='diff-marker'>−</td><td style="color:black; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #ffe49c; vertical-align: top; white-space: pre-wrap;"><div><del style="font-weight: bold; text-decoration: none;"></del></div></td><td colspan="2">&#160;</td></tr> <tr><td class='diff-marker'>&#160;</td><td style="background-color: #f9f9f9; color: #333333; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #e6e6e6; vertical-align: top; white-space: pre-wrap;"></td><td class='diff-marker'>&#160;</td><td style="background-color: #f9f9f9; color: #333333; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #e6e6e6; vertical-align: top; white-space: pre-wrap;"></td></tr> <tr><td class='diff-marker'>&#160;</td><td style="background-color: #f9f9f9; color: #333333; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #e6e6e6; vertical-align: top; white-space: pre-wrap;"></td><td class='diff-marker'>&#160;</td><td style="background-color: #f9f9f9; color: #333333; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #e6e6e6; vertical-align: top; white-space: pre-wrap;"></td></tr> <tr><td colspan="2" class="diff-lineno">第27行：</td> <td colspan="2" class="diff-lineno">第26行：</td></tr> <tr><td class='diff-marker'>&#160;</td><td style="background-color: #f9f9f9; color: #333333; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #e6e6e6; vertical-align: top; white-space: pre-wrap;"><div>==开发者资源==</div></td><td class='diff-marker'>&#160;</td><td style="background-color: #f9f9f9; color: #333333; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #e6e6e6; vertical-align: top; white-space: pre-wrap;"><div>==开发者资源==</div></td></tr> <tr><td class='diff-marker'>&#160;</td><td style="background-color: #f9f9f9; color: #333333; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #e6e6e6; vertical-align: top; white-space: pre-wrap;"></td><td class='diff-marker'>&#160;</td><td style="background-color: #f9f9f9; color: #333333; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #e6e6e6; vertical-align: top; white-space: pre-wrap;"></td></tr> <tr><td class='diff-marker'>−</td><td style="color:black; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #ffe49c; vertical-align: top; white-space: pre-wrap;"><div>&#160;</div></td><td class='diff-marker'>+</td><td style="color:black; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #a3d3ff; vertical-align: top; white-space: pre-wrap;"><div><ins class="diffchange diffchange-inline">* Dataset [https://datadryad.org/stash/dataset/doi:10.5061/dryad.2hp1978]</ins></div></td></tr> <tr><td class='diff-marker'>&#160;</td><td style="background-color: #f9f9f9; color: #333333; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #e6e6e6; vertical-align: top; white-space: pre-wrap;"></td><td class='diff-marker'>&#160;</td><td style="background-color: #f9f9f9; color: #333333; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #e6e6e6; vertical-align: top; white-space: pre-wrap;"></td></tr> <tr><td class='diff-marker'>&#160;</td><td style="background-color: #f9f9f9; color: #333333; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #e6e6e6; vertical-align: top; white-space: pre-wrap;"><div>==高级读者==</div></td><td class='diff-marker'>&#160;</td><td style="background-color: #f9f9f9; color: #333333; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #e6e6e6; vertical-align: top; white-space: pre-wrap;"><div>==高级读者==</div></td></tr> <tr><td colspan="2">&#160;</td><td class='diff-marker'>+</td><td style="color:black; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #a3d3ff; vertical-align: top; white-space: pre-wrap;"><div><ins style="font-weight: bold; text-decoration: none;"></ins></div></td></tr> <tr><td colspan="2">&#160;</td><td class='diff-marker'>+</td><td style="color:black; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #a3d3ff; vertical-align: top; white-space: pre-wrap;"><div><ins style="font-weight: bold; text-decoration: none;">* Hoyal Cuthill J F, Guttenberg N, Ledger S, et al. Deep learning on butterfly phenotypes tests evolution’s oldest mathematical model[J]. Science advances, 2019, 5(8): eaaw4967. [https://www.science.org/doi/pdf/10.1126/sciadv.aaw4967]</ins></div></td></tr> <tr><td colspan="2">&#160;</td><td class='diff-marker'>+</td><td style="color:black; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #a3d3ff; vertical-align: top; white-space: pre-wrap;"><div><ins style="font-weight: bold; text-decoration: none;">* MuÈller, F. Ituna and Thyridia; a remarkable case of mimicry in butteries. Trans. Ent. Soc. Lond. 1879, </ins></div></td></tr> <tr><td colspan="2">&#160;</td><td class='diff-marker'>+</td><td style="color:black; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #a3d3ff; vertical-align: top; white-space: pre-wrap;"><div><ins style="font-weight: bold; text-decoration: none;">* Saitou N, Nei M. The neighbor-joining method: a new method for reconstructing phylogenetic trees[J]. Molecular biology and evolution, 1987, 4(4): 406-425. [https://academic.oup.com/mbe/article-pdf/4/4/406/11167444/7sait.pdf]</ins></div></td></tr> <tr><td colspan="2">&#160;</td><td class='diff-marker'>+</td><td style="color:black; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #a3d3ff; vertical-align: top; white-space: pre-wrap;"><div><ins style="font-weight: bold; text-decoration: none;">* Richard M.MerrillChris D.Jiggins, Müllerian Mimicry: Sharing the Load Reduces the Legwork[https://www.sciencedirect.com/science/article/pii/S096098220901389X]</ins></div></td></tr> </table>

Cslt http://www.cslt.org/mediawiki/index.php?title=%E7%AC%AC%E4%B8%89%E5%8D%81%E4%B9%9D%E7%AB%A0_%E7%94%9F%E7%89%A9%E6%8B%9F%E6%80%81%E8%AF%81%E6%8D%AE&diff=39150&oldid=prev 2022-08-22T07:33:06Z

<p>以“==教学资料== * <a href="/mediawiki/index.php/%E6%95%99%E5%AD%A6%E5%8F%82%E8%80%83-39" title="教学参考-39">教学参考</a> * [http://aigraph.cslt.org/courses/39/course-39.pptx 课件] * 小清爱提问：机器学习如何发现生物...”为内容创建页面</p> <p><b>新页面</b></p><div>==教学资料==<br /> <br /> * [[教学参考-39|教学参考]]<br /> * [http://aigraph.cslt.org/courses/39/course-39.pptx 课件]<br /> * 小清爱提问：机器学习如何发现生物拟态证据？ []<br /> <br /> <br /> ==扩展阅读==<br /> <br /> * AI100问：机器学习如何发现生物拟态证据？[http://aigraph.cslt.org/ai100/AI-100-28-机器学习如何发现生物拟态证据.pdf]<br /> * 维基百科：生物拟态[http://aigraph.cslt.org/courses/39/拟态.pdf][http://aigraph.cslt.org/courses/39/Mimicry.pdf]<br /> <br /> <br /> ==视频展示==<br /> <br /> * 生物的拟态 [https://www.bilibili.com/video/BV1wq4y1w7HD?spm_id_from=333.337.search-card.all.click]<br /> * 你肯定以为这是树叶，那你就错了，动物的拟态能力会超乎你想象 [https://www.bilibili.com/video/BV1Lt411r7kp?spm_id_from=333.337.search-card.all.click]<br /> * 会拟态的动物合集 [https://www.bilibili.com/video/BV1G5411t7DR?spm_id_from=333.337.search-card.all.click]<br /> * 拟态专家大赏 [https://www.bilibili.com/video/BV1Zh411B7bu?spm_id_from=333.337.search-card.all.click]<br /> <br /> <br /> <br /> <br /> ==演示链接==<br /> <br /> <br /> ==开发者资源==<br /> <br /> <br /> <br /> ==高级读者==</div>

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