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公开(公告)号：US20170228633A1
公开(公告)日：2017-08-10
申请号：US15424708
申请日：2017-02-03
Applicant: Google Inc.
Inventor： Ivo Danihelka , Danilo Jimenez Rezende , Shakir Mohamed
CPC classification number: G06N3/0445 , G06K9/6257 , G06K9/66 , G06N3/0472 , G06N3/084
Abstract: Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for a neural network system. In one aspect, a neural network system includes a recurrent neural network that is configured to, for each time step of a predetermined number of time steps, receive a set of latent variables for the time step and process the latent variables to update a hidden state of the recurrent neural network; and a generative subsystem that is configured to, for each time step, generate the set of latent variables for the time step and provide the set of latent variables as input to the recurrent neural network; update a hidden canvas using the updated hidden state of the recurrent neural network; and, for a last time step, generate an output image using the updated hidden canvas for the last time step.
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公开(公告)号：US09342781B2
公开(公告)日：2016-05-17
申请号：US13925637
申请日：2013-06-24
Applicant: Google Inc.
CPC classification number: G06N3/0454 , G06N3/084
Abstract: We describe a signal processor, the signal processor comprising: a probability vector generation system, wherein said probability vector generation system has an input to receive a category vector for a category of output example and an output to provide a probability vector for said category of output example, wherein said output example comprises a set of data points, and wherein said probability vector defines a probability of each of said set of data points for said category of output example; a memory storing a plurality of said category vectors, one for each of a plurality of said categories of output example; and a stochastic selector to select a said stored category of output example for presentation of the corresponding category vector to said probability vector generation system; wherein said signal processor is configured to output data for an output example corresponding to said selected stored category.
Abstract translation: 我们描述信号处理器，信号处理器包括：概率向量生成系统，其中所述概率向量生成系统具有用于接收输出示例类别的类别向量的输入和输出，以为所述输出类别提供概率向量 示例，其中所述输出示例包括一组数据点，并且其中所述概率向量定义所述类别的输出示例的所述数据点集合中的每一个的概率; 存储多个所述类别矢量的存储器，一个用于多个所述类别的输出示例中的每一个; 以及随机选择器，用于选择所述存储的类别的输出示例，以将对应的类别向量呈现给所述概率向量生成系统; 其中所述信号处理器被配置为输出对应于所述选择的存储类别的输出示例的数据。
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公开(公告)号：US20140279777A1
公开(公告)日：2014-09-18
申请号：US13925637
申请日：2013-06-24
Applicant: Google Inc.
CPC classification number: G06N3/0454 , G06N3/084
Abstract: We describe a signal processor, the signal processor comprising: a probability vector generation system, wherein said probability vector generation system has an input to receive a category vector for a category of output example and an output to provide a probability vector for said category of output example, wherein said output example comprises a set of data points, and wherein said probability vector defines a probability of each of said set of data points for said category of output example; a memory storing a plurality of said category vectors, one for each of a plurality of said categories of output example; and a stochastic selector to select a said stored category of output example for presentation of the corresponding category vector to said probability vector generation system; wherein said signal processor is configured to output data for an output example corresponding to said selected stored category.
Abstract translation: 我们描述信号处理器，信号处理器包括：概率向量生成系统，其中所述概率向量生成系统具有用于接收输出示例类别的类别向量的输入和输出，以为所述输出类别提供概率向量 示例，其中所述输出示例包括一组数据点，并且其中所述概率向量定义所述类别的输出示例的所述数据点集合中的每一个的概率; 存储多个所述类别矢量的存储器，一个用于多个所述类别的输出示例中的每一个; 以及随机选择器，用于选择所述存储的类别的输出示例，以将对应的类别向量呈现给所述概率向量生成系统; 其中所述信号处理器被配置为输出对应于所述选择的存储类别的输出示例的数据。
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