图 书 馆
为动态不变量挖掘实验数据——从认知机器人到计算生物学Mining experimental data for dynamical invariants - from cognitive robotics to computational biology |
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| 课程网址: | http://videolectures.net/ecmlpkdd2010_lipson_med/ |
| 主讲教师: | Hod Lipson |
| 开课单位: | 康奈尔大学 |
| 开课时间: | 2010-11-16 |
| 课程语种: | 英语 |
| 中文简介: |  |
| 课程简介: | For centuries, scientists have attempted to identify and document analytical laws that underlie physical phenomena in nature. Despite the prevalence of computing power, the process of finding natural laws and their corresponding equations has resisted automation. A key challenge to finding analytic relations automatically is defining algorithmically what makes a correlation in observed data important and insightful. By seeking dynamical invariants, we go from finding just predictive models to finding deeper conservation laws. We demonstrated this approach by automatically searching motion-tracking data captured from various physical systems, ranging from simple harmonic oscillators to chaotic double-pendula. Without any prior knowledge about physics, kinematics, or geometry, the algorithm discovered Hamiltonians, Lagrangians, and other laws of geometric and momentum conservation. The discovery rate accelerated as laws found for simpler systems were used to bootstrap explanations for more complex systems, gradually uncovering the "alphabet" used to describe those systems. Applications to modeling physical and biological systems will be shown. |
| 关 键 词: | 自动查找分析; 计算机算法; 物理定律; 简谐振荡器; 哈密顿量; 拉格朗日量; 生物物理系统建模 |
| 课程来源: | 视频讲座网 |
| 最后编审: | 2019-10-17：cwx |
| 阅读次数: | 50 |