图 书 馆
图形模型中的推理Inference in Graphical Models |
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| 课程网址: | http://videolectures.net/mlss08au_caetano_grmo/ |
| 主讲教师: | Tibério Caetano |
| 开课单位: | 澳大利亚信息通信技术研究中心 |
| 开课时间: | 2008-03-12 |
| 课程语种: | 英语 |
| 中文简介: |  |
| 课程简介: | This short course will cover the basics of inference in graphical models. It will start by explaining the theory of probabilistic graphical models, including concepts of conditional independence and factorisation and how they arise in both Markov random fields and Bayesian Networks. He will then present the fundamental methods for performing exact probabilistic inference in such models, which include algorithms like variable elimination, belief propagation and Junction Trees. He will also briefly discuss some of the current methods for performing approximate inference when exact inference is not feasible. Finally, he will illustrate a range of real problems whose solutions can be formulated as inference in graphical models. |
| 关 键 词: | 图形推理; 贝叶斯网络交叉树 |
| 课程来源: | 视频讲座网 |
| 最后编审: | 2021-01-15：yumf |
| 阅读次数: | 98 |