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1. 发明申请

WO2018211145A1 GENERATING OUTPUT EXAMPLES USING BIT BLOCKS 审中-公开
公开(公告)号：WO2018211145A1
公开(公告)日：2018-11-22
申请号：PCT/EP2018/063305
申请日：2018-05-22
申请人： DEEPMIND TECHNOLOGIES LIMITED
发明人： KALCHBRENNER, Nal Emmerich , SIMONYAN, Karen , ELSEN, Erich Konrad
IPC分类号： G06N3/04 , G06N3/08
摘要： Methods, systems, and apparatus, including computer programs encoded on computer storage media, for generating output examples using neural networks. One of the methods includes receiving a request to generate an output example of a particular type, accessing dependency data, and generating the output example by, at each of a plurality of generation time steps: identifying one or more current blocks for the generation time step, wherein each current block is a block for which the values of the bits in all of the other blocks identified in the dependency for the block have already been generated; and generating the values of the bits in the current blocks for the generation time step conditioned on, for each current block, the already generated values of the bits in the other blocks identified in the dependency for the current block.

2. 发明申请

WO2018048945A1 PROCESSING SEQUENCES USING CONVOLUTIONAL NEURAL NETWORKS 审中-公开
标题翻译：用卷积神经网络处理序列
公开(公告)号：WO2018048945A1
公开(公告)日：2018-03-15
申请号：PCT/US2017/050335
申请日：2017-09-06
申请人： DEEPMIND TECHNOLOGIES LIMITED
发明人： VAN DEN OORD, Aaron Gerard Antonius , DIELEMAN, Sander Etienne Lea , KALCHBRENNER, Nal Emmerich , SIMONYAN, Karen , VINYALS, Oriol , ESPEHOLT, Lasse
IPC分类号： G06N3/04
摘要： Methods, systems, and apparatus, including computer programs encoded on computer storage media, for generating of generating a neural network output from an input sequence. One of the methods includes, for each of the inputs, providing a current input sequence that comprises the input and the inputs preceding the input in the input sequence to a convolutional subnetwork comprising a plurality of dilated convolutional neural network layers, wherein the convolutional subnetwork is configured to, for each of the plurality of inputs: receive the current input sequence for the input, and process the current input sequence to generate an alternative representation for the input; and providing the alternative representations to an output subnetwork, wherein the output subnetwork is configured to receive the alternative representations and to process the alternative representations to generate the neural network output.
摘要翻译：包括在计算机存储介质上编码的计算机程序的方法，系统和装置，用于从输入序列产生神经网络输出。其中一种方法包括对于每个输入提供当前输入序列，该输入序列包括输入和输入之前的输入之前的输入到包括多个膨胀卷积神经网络层的卷积子网络，其中卷积子网络是被配置为针对所述多个输入中的每一个：接收所述输入的当前输入序列，并且处理所述当前输入序列以生成所述输入的替代表示; 以及将所述替代表示提供给输出子网络，其中所述输出子网络被配置为接收所述替代表示并处理所述替代表示以生成所述神经网络输出。

3. 发明申请

WO2020069449A1 IMAGE GENERATION USING SUBSCALING AND DEPTH UP-SCALING 审中-公开
公开(公告)号：WO2020069449A1
公开(公告)日：2020-04-02
申请号：PCT/US2019/053666
申请日：2019-09-27
申请人： DEEPMIND TECHNOLOGIES LIMITED
发明人： KALCHBRENNER, Nal Emmerich , MENICK, Jacob Lee
IPC分类号： G06T11/00
摘要： Methods, systems, and apparatus, including computer programs encoded on computer storage media, for generating output images. One of the methods includes obtaining data specifying (i) a partitioning of the H by W pixel grid of the output image into K disjoint, interleaved sub-images and (ii) an ordering of the sub-images; and generating intensity values sub-image by sub-image, comprising: for each particular color channel for each particular pixel in each particular sub-image, generating, using a generative neural network, the intensity value for the particular color channel conditioned on intensity values for (i) any pixels that are in sub-images that are before the particular sub-image in the ordering, (ii) any pixels within the particular sub-image that are before the particular pixel in a raster-scan order over the output image, and (iii) the particular pixel for any color channels that are before the particular color channel in a color channel order.

4. 发明申请

WO2019155054A1 GENERATING OUTPUT EXAMPLES USING RECURRENT NEURAL NETWORKS CONDITIONED ON BIT VALUES 审中-公开
公开(公告)号：WO2019155054A1
公开(公告)日：2019-08-15
申请号：PCT/EP2019/053300
申请日：2019-02-11
申请人： DEEPMIND TECHNOLOGIES LIMITED
发明人： KALCHBRENNER, Nal Emmerich , SIMONYAN, Karen , ELSEN, Erich Konrad
IPC分类号： G06N3/04
CPC分类号： G06N3/0445
摘要： Methods, systems, and apparatus, including computer programs encoded on computer storage media, for generating output examples using neural networks. One of the methods includes, at each generation time step, processing a first recurrent input comprising an N-bit output value at the preceding generation time step in the sequence using a recurrent neural network and in accordance with a hidden state to generate a first score distribution; selecting, using the first score distribution, values for the first half of the N bits; processing a second recurrent input comprising (i) the N-bit output value at the preceding generation time step and (ii) the values for the first half of the N bits using the recurrent neural network and in accordance with the same hidden state to generate a second score distribution; and selecting, using the second score distribution, values for the second half of the N bits of the output value.

5. 发明申请

WO2018048934A1 GENERATING AUDIO USING NEURAL NETWORKS 审中-公开
标题翻译：用神经网络产生音频
公开(公告)号：WO2018048934A1
公开(公告)日：2018-03-15
申请号：PCT/US2017/050320
申请日：2017-09-06
申请人： DEEPMIND TECHNOLOGIES LIMITED
发明人： VAN DEN OORD, Aaron Gerard Antonius , DIELEMAN, Sander Etienne Lea , KALCHBRENNER, Nal Emmerich , SIMONYAN, Karen , VINYALS, Oriol
IPC分类号： G06N3/04
摘要： Methods, systems, and apparatus, including computer programs encoded on computer storage media, for generating an output sequence of audio data that comprises a respective audio sample at each of a plurality of time steps. One of the methods includes, for each of the time steps: providing a current sequence of audio data as input to a convolutional subnetwork, wherein the current sequence comprises the respective audio sample at each time step that precedes the time step in the output sequence, and wherein the convolutional subnetwork is configured to process the current sequence of audio data to generate an alternative representation for the time step; and providing the alternative representation for the time step as input to an output layer, wherein the output layer is configured to: process the alternative representation to generate an output that defines a score distribution over a plurality of possible audio samples for the time step.
摘要翻译：包括在计算机存储介质上编码的计算机程序的方法，系统和装置，用于生成音频数据的输出序列，该音频数据的输出序列在多个时间步骤中的每个时间步骤包括相应的音频样本。对于每个时间步骤，这些方法之一包括：提供音频数据的当前序列作为卷积子网络的输入，其中当前序列包括在输出序列中的时间步长之前的每个时间步骤处的相应音频样本，且其中所述卷积子网络经配置以处理所述当前音频数据序列以产生所述时间步骤的替代表示; 以及将所述时间步长的所述替代表示作为输入提供给输出层，其中所述输出层被配置为：处理所述替代表示以产生定义所述时间步骤的多个可能音频样本上的得分分布的输出。 / p>

6. 发明申请

WO2018154092A8 ITERATIVE MULTISCALE IMAGE GENERATION USING NEURAL NETWORKS 审中-公开
公开(公告)号：WO2018154092A8
公开(公告)日：2018-08-30
申请号：PCT/EP2018/054614
申请日：2018-02-26
申请人： DEEPMIND TECHNOLOGIES LIMITED
发明人： KALCHBRENNER, Nal Emmerich , BELOV, Daniel , GOMEZ COLMENAREJO, Sergio , VAN DEN OORD, Aaron Gerard Antonius , WANG, Ziyu , GOMES DE FREITAS, Joao Ferdinando , REED, Scott Ellison
IPC分类号： G06T3/40
摘要： A method of generating an output image having an output resolution of N pixels x N pixels, each pixel in the output image having a respective color value for each of a plurality of color channels, the method comprising: obtaining a low-resolution version of the output image; and upscaling the low-resolution version of the output image to generate the output image having the output resolution by repeatedly performing the following operations: obtaining a current version of the output image having a current K x K resolution; and processing the current version of the output image using a set of convolutional neural networks that are specific to the current resolution to generate an updated version of the output image having a 2K x 2K resolution.

7. 发明申请

WO2018154092A1 MULTISCALE IMAGE GENERATION 审中-公开
公开(公告)号：WO2018154092A1
公开(公告)日：2018-08-30
申请号：PCT/EP2018/054614
申请日：2018-02-26
申请人： DEEPMIND TECHNOLOGIES LIMITED
发明人： KALCHBRENNER, Nal Emmerich , BELOV, Daniel , GOMEZ COLMENAREJO, Sergio , VAN DEN OORD, Aaron Gerard Antonius , WANG, Ziyu , GOMES DE FREITAS, Joao Ferdinando , REED, Scott Ellison
IPC分类号： G06T3/40
摘要： A method of generating an output image having an output resolution of N pixels x N pixels, each pixel in the output image having a respective color value for each of a plurality of color channels, the method comprising: obtaining a low-resolution version of the output image; and upscaling the low-resolution version of the output image to generate the output image having the output resolution by repeatedly performing the following operations: obtaining a current version of the output image having a current K x K resolution; and processing the current version of the output image using a set of convolutional neural networks that are specific to the current resolution to generate an updated version of the output image having a 2K x 2K resolution.

8. 发明申请

WO2018081089A1 PROCESSING TEXT SEQUENCES USING NEURAL NETWORKS 审中-公开
标题翻译：用神经网络处理文本序列
公开(公告)号：WO2018081089A1
公开(公告)日：2018-05-03
申请号：PCT/US2017/058046
申请日：2017-10-24
申请人： DEEPMIND TECHNOLOGIES LIMITED
发明人： KALCHBRENNER, Nal Emmerich , SIMONYAN, Karen , ESPEHOLT, Lasse
IPC分类号： G06N3/04 , G06F17/20
摘要： Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for neural machine translation. In one aspect, a system is configured to receive an input sequence of source embeddings representing a source sequence of words in a source natural language and to generate an output sequence of target embeddings representing a target sequence of words that is a translation of the source sequence into a target natural language, the system comprising: a dilated convolutional neural network configured to process the input sequence of source embeddings to generate an encoded representation of the source sequence, and a masked dilated convolutional neural network configured to process the encoded representation of the source sequence to generate the output sequence of target embeddings.
摘要翻译：包括编码在计算机存储介质上的计算机程序的方法，系统和装置用于神经机器翻译。在一个方面中，系统被配置为接收表示源自然语言中的源的源序列的输入序列的源嵌入，并且生成表示作为源序列的翻译的词的目标序列的输出序列的目标嵌入转换成目标自然语言，所述系统包括：扩张的卷积神经网络，其被配置为处理源输入序列的源嵌入以生成源序列的编码表示;以及掩蔽的扩张卷积神经网络，其被配置为处理源的编码表示序列来生成目标嵌入的输出序列。

9. 发明申请

WO2018064591A1 GENERATING VIDEO FRAMES USING NEURAL NETWORKS 审中-公开
标题翻译：用神经网络生成视频帧
公开(公告)号：WO2018064591A1
公开(公告)日：2018-04-05
申请号：PCT/US2017/054528
申请日：2017-09-29
申请人： DEEPMIND TECHNOLOGIES LIMITED
发明人： KALCHBRENNER, Nal Emmerich , VAN DEN OORD, Aaron Gerard Antonius , SIMONYAN, Karen
IPC分类号： G06N3/04
CPC分类号： G06N3/0454 , G06N3/0445
摘要： Methods, systems, and apparatus, including computer programs encoded on computer storage media, for generating video frames using neural networks. One of the methods includes processing a sequence of video frames using an encoder neural network to generate an encoded representation; and generating a predicted next frame pixel by pixel according to a pixel order and a channel order, comprising: for each color channel of each pixel, providing as input to a decoder neural network (i) the encoded representation, (ii) color values for any pixels before the pixel in the pixel order, and (iii) color values for the pixel for any color channels before the color channel in the channel order, wherein the decoder neural network is configured to generate an output defining a score distribution over a plurality of possible color values, and determining the color value for the color channel of the pixel by sampling from the score distribution.
摘要翻译：包括在计算机存储介质上编码的计算机程序的方法，系统和装置，用于使用神经网络产生视频帧。其中一种方法包括使用编码器神经网络处理视频帧序列以生成编码表示; 包括：对于每个像素的每个颜色通道，提供作为解码器神经网络的输入（i）所述编码表示，（ii）针对每个像素的颜色值，以及并且（iii）在通道顺序中的颜色通道之前的任何颜色通道的像素的颜色值，其中解码器神经网络被配置为生成定义多个分数分布的输出可能的颜色值，并且通过从分数分布抽样来确定像素的颜色通道的颜色值。

10. 发明公开

EP3625732A1 GENERATING OUTPUT EXAMPLES USING BIT BLOCKS 审中-公开
公开(公告)号：EP3625732A1
公开(公告)日：2020-03-25
申请号：EP18726786.9
申请日：2018-05-22
申请人： Deepmind Technologies Limited
发明人： KALCHBRENNER, Nal Emmerich , SIMONYAN, Karen , ELSEN, Erich Konrad
IPC分类号： G06N3/04 , G06N3/08

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