Restricted Quasi Bayesian Networks as a Prototyping Tool for Computational Models of Individual Cortical Areas
Restricted Quasi Bayesian Networks as a Prototyping Tool for Computational Models of Individual Cortical Areas
复制标题
受限拟贝叶斯网络作为单个皮质区域计算模型的原型工具
DOI：
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发表时间：
2017
期刊：
影响因子：
--
通讯作者：
Yuuji Ichisugi
中科院分区：
文献类型：
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作者：
N. Takahashi;Yuuji Ichisugi
我们提出限制准贝叶斯网络作为一种有效的原型工具，用于设计单个大脑皮层区域的计算模型。受限拟贝叶斯网络是只区分概率值0和其他值的简化贝叶斯网络。使用我们的工具，可以专注于模型设计的基本部分，并有效地构建原型。我们通过为歧义的英语句子实现语法解析器，证明了受限的准贝叶斯网络实际上可以很好地作为原型工具。
We propose restricted quasi Bayesian networks as an efficient prototyping tool for designing computational models of individual cortical areas of the brain. Restricted quasi Bayesian networks are simplified Bayesian networks that only distinguish probability value 0 from other values. Using our tool, it is possible to concentrate on the essential part of model design and efficiently construct prototypes. We demonstrate that restricted quasi Bayesian networks actually work well as a prototyping tool by implementing a syntactic parser for an ambiguous English sentence.
DOI：
10.1364/josaa.20.001434
发表时间：
2003-07-01
影响因子：
1.9
作者：
Lee, TS;Mumford, D
通讯作者：
Mumford, D