公开(公告)号：US11870947B2

公开(公告)日：2024-01-09

申请号：US17959132

申请日：2022-10-03

Applicant: DeepMind Technologies Limited

Inventor： Aaron Gerard Antonius van den Oord ,  Nal Emmerich Kalchbrenner ,  Karen Simonyan

IPC: H04N19/50 ,  H04N19/52 ,  H04N19/56 ,  G06N3/04 ,  G06N3/08 ,  G06F18/21 ,  G06V10/56 ,  G06V30/19 ,  G06N3/084 ,  G06F18/2113 ,  G06N3/044 ,  G06N3/045 ,  G06V30/194 ,  H04N19/186 ,  H04N19/172 ,  H04N19/182

CPC classification number: H04N19/50 ,  G06F18/2113 ,  G06N3/04 ,  G06N3/044 ,  G06N3/045 ,  G06N3/08 ,  G06N3/084 ,  G06V10/56 ,  G06V30/194 ,  H04N19/52 ,  H04N19/172 ,  H04N19/182 ,  H04N19/186

Abstract: Methods, systems, and apparatus, including computer programs encoded on computer storage media, for generating images using neural networks. One of the methods includes generating the output image pixel by pixel from a sequence of pixels taken from the output image, comprising, for each pixel in the output image, generating a respective score distribution over a discrete set of possible color values for each of the plurality of color channels.

公开(公告)号：US11756561B2

公开(公告)日：2023-09-12

申请号：US17674752

申请日：2022-02-17

Applicant: DeepMind Technologies Limited

Inventor： Cristina Garbacea ,  Aaron Gerard Antonius van den Oord ,  Yazhe Li ,  Sze Chie Lim ,  Alejandro Luebs ,  Oriol Vinyals ,  Thomas Chadwick Walters

IPC: G10L19/16 ,  G10L19/032 ,  G10L25/30 ,  G06N3/08

CPC classification number: G10L19/16 ,  G06N3/08 ,  G10L19/032 ,  G10L25/30

Abstract: Methods, systems, and apparatus, including computer programs encoded on computer storage media, for generating discrete latent representations of input audio data. Only the discrete latent representation needs to be transmitted from an encoder system to a decoder system in order for the decoder system to be able to effectively to decode, i.e., reconstruct, the input audio data.

公开(公告)号：US20230274125A1

公开(公告)日：2023-08-31

申请号：US18090243

申请日：2022-12-28

Applicant: DeepMind Technologies Limited

Inventor： Aaron Gerard Antonius van den Oord ,  Yazhe Li ,  Oriol Vinyals

IPC: G06N3/006 ,  G06F17/16 ,  G06N3/08 ,  G06F18/22 ,  G06N3/045 ,  G06N3/048 ,  G06V10/764 ,  G06V10/77 ,  G06V10/82

CPC classification number: G06N3/006 ,  G06F17/16 ,  G06N3/08 ,  G06F18/22 ,  G06N3/045 ,  G06N3/048 ,  G06V10/764 ,  G06V10/7715 ,  G06V10/82

Abstract: Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for training an encoder neural network that is configured to process an input observation to generate a latent representation of the input observation. In one aspect, a method includes: obtaining a sequence of observations; for each observation in the sequence of observations, processing the observation using the encoder neural network to generate a latent representation of the observation; for each of one or more given observations in the sequence of observations: generating a context latent representation of the given observation; and generating, from the context latent representation of the given observation, a respective estimate of the latent representations of one or more particular observations that are after the given observation in the sequence of observations.

公开(公告)号：US11462034B2

公开(公告)日：2022-10-04

申请号：US17198096

申请日：2021-03-10

Applicant: DeepMind Technologies Limited

Inventor： Aaron Gerard Antonius van den Oord ,  Nal Emmerich Kalchbrenner ,  Karen Simonyan

IPC: G06V30/194 ,  G06N3/04 ,  G06N3/08 ,  H04N19/52 ,  H04N19/50 ,  G06V10/56 ,  H04N19/186 ,  H04N19/172 ,  H04N19/182 ,  G06K9/62

Abstract: Methods, systems, and apparatus, including computer programs encoded on computer storage media, for generating images using neural networks. One of the methods includes generating the output image pixel by pixel from a sequence of pixels taken from the output image, comprising, for each pixel in the output image, generating a respective score distribution over a discrete set of possible color values for each of the plurality of color channels.

公开(公告)号：US11361403B2

公开(公告)日：2022-06-14

申请号：US16324061

申请日：2018-02-26

Applicant: DeepMind Technologies Limited

Inventor： Nal Emmerich Kalchbrenner ,  Daniel Belov ,  Sergio Gomez Colmenarejo ,  Aaron Gerard Antonius van den Oord ,  Ziyu Wang ,  Joao Ferdinando Gomes de Freitas ,  Scott Ellison Reed

IPC: G06T3/40 ,  G06N20/00 ,  G06N3/04

Abstract: A method of generating an output image having an output resolution of N pixels×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×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×2K resolution.

公开(公告)号：US11080591B2

公开(公告)日：2021-08-03

申请号：US15697407

申请日：2017-09-06

Applicant: DeepMind Technologies Limited

Inventor： Aaron Gerard Antonius van den Oord ,  Sander Etienne Lea Dieleman ,  Nal Emmerich Kalchbrenner ,  Karen Simonyan ,  Oriol Vinyals ,  Lasse Espeholt

IPC: G06N3/04 ,  G10L15/16 ,  G10L13/08 ,  G10L25/30 ,  G10L13/04 ,  G06N3/08 ,  G06F40/44 ,  G06F40/279 ,  G06F17/18

Abstract: Methods, systems, and apparatus, including computer programs encoded on computer storage media, for processing sequences using convolutional neural networks. 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.

公开(公告)号：US20200234725A1

公开(公告)日：2020-07-23

申请号：US16746703

申请日：2020-01-17

Applicant: DeepMind Technologies Limited

Inventor： Cristina Garbacea ,  Aaron Gerard Antonius van den Oord ,  Yazhe Li ,  Sze Chie Lim ,  Alejandro Luebs ,  Oriol Vinyals ,  Thomas Chadwick Walters

IPC: G10L19/16 ,  G10L19/032 ,  G10L25/30 ,  G06N3/08

Abstract: Methods, systems, and apparatus, including computer programs encoded on computer storage media, for generating discrete latent representations of input audio data. Only the discrete latent representation needs to be transmitted from an encoder system to a decoder system in order for the decoder system to be able to effectively to decode, i.e., reconstruct, the input audio data.

公开(公告)号：US20240412042A1

公开(公告)日：2024-12-12

申请号：US18698260

申请日：2022-10-06

Applicant: DeepMind Technologies Limited

Inventor： Nikolay Savinov ,  Junyoung Chung ,  Mikolaj Binkowski ,  Aaron Gerard Antonius van den Oord ,  Erich Konrad Elsen

IPC: G06N3/0455 ,  G06N3/08

Abstract: Methods, systems, and apparatus, including computer programs encoded on computer storage media, for generating output sequences using a non-auto-regressive neural network.

公开(公告)号：US20240346285A1

公开(公告)日：2024-10-17

申请号：US18607777

申请日：2024-03-18

Applicant: DeepMind Technologies Limited

Inventor： Aaron Gerard Antonius van den Oord ,  Karen Simonyan ,  Oriol Vinyals

IPC: G06N3/04 ,  G06N3/045 ,  G06N3/08 ,  G06N3/088 ,  G10L13/00

CPC classification number: G06N3/04 ,  G06N3/045 ,  G06N3/08 ,  G06N3/088 ,  G10L13/00

Abstract: A feedforward generative neural network that generates an output example that includes multiple output samples of a particular type in a single neural network inference. Optionally, the generation may be conditioned on a context input. For example, the feedforward generative neural network may generate a speech waveform that is a verbalization of an input text segment conditioned on linguistic features of the text segment.

公开(公告)号：US20240273333A1

公开(公告)日：2024-08-15

申请号：US18640741

申请日：2024-04-19

Applicant: DeepMind Technologies Limited

Inventor： Aaron Gerard Antonius van den Oord ,  Yazhe Li ,  Oriol Vinyals

IPC: G06N3/006 ,  G06F17/16 ,  G06F18/22 ,  G06N3/045 ,  G06N3/048 ,  G06N3/08 ,  G06V10/764 ,  G06V10/77 ,  G06V10/82

CPC classification number: G06N3/006 ,  G06F17/16 ,  G06F18/22 ,  G06N3/045 ,  G06N3/048 ,  G06N3/08 ,  G06V10/764 ,  G06V10/7715 ,  G06V10/82

Abstract: Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for training an encoder neural network that is configured to process an input observation to generate a latent representation of the input observation. In one aspect, a method includes: obtaining a sequence of observations; for each observation in the sequence of observations, processing the observation using the encoder neural network to generate a latent representation of the observation; for each of one or more given observations in the sequence of observations: generating a context latent representation of the given observation; and generating, from the context latent representation of the given observation, a respective estimate of the latent representations of one or more particular observations that are after the given observation in the sequence of observations.