公开(公告)号：US11734572B2

公开(公告)日：2023-08-22

申请号：US16995307

申请日：2020-08-17

Applicant: DeepMind Technologies Limited

Inventor： Maxwell Elliot Jaderberg ,  Karen Simonyan ,  Andrew Zisserman ,  Koray Kavukcuoglu

IPC: G06N3/045 ,  G06N3/088 ,  G06N3/084 ,  G06V10/44

CPC classification number: G06N3/084 ,  G06N3/045 ,  G06N3/088 ,  G06V10/454

Abstract: Methods, systems, and apparatus, including computer programs encoded on computer storage media, for processing inputs using an image processing neural network system that includes a spatial transformer module. One of the methods includes receiving an input feature map derived from the one or more input images, and applying a spatial transformation to the input feature map to generate a transformed feature map, comprising: processing the input feature map to generate spatial transformation parameters for the spatial transformation, and sampling from the input feature map in accordance with the spatial transformation parameters to generate the transformed feature map.

公开(公告)号：US11593646B2

公开(公告)日：2023-02-28

申请号：US16767049

申请日：2019-02-05

Applicant: DeepMind Technologies Limited

Inventor： Hubert Josef Soyer ,  Lasse Espeholt ,  Karen Simonyan ,  Yotam Doron ,  Vlad Firoiu ,  Volodymyr Mnih ,  Koray Kavukcuoglu ,  Remi Munos ,  Thomas Ward ,  Timothy James Alexander Harley ,  Iain Robert Dunning

IPC: G06N3/08 ,  G06N3/04

Abstract: Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for training an action selection neural network used to select actions to be performed by an agent interacting with an environment. In one aspect, a system comprises a plurality of actor computing units and a plurality of learner computing units. The actor computing units generate experience tuple trajectories that are used by the learner computing units to update learner action selection neural network parameters using a reinforcement learning technique. The reinforcement learning technique may be an off-policy actor critic reinforcement learning technique.

公开(公告)号：US20210256375A1

公开(公告)日：2021-08-19

申请号：US17169083

申请日：2021-02-05

Applicant: DeepMind Technologies Limited

Inventor： Jacob Lee Menick ,  Erich Konrad Elsen ,  Karen Simonyan

IPC: G06N3/08 ,  G06N3/04

Abstract: A computer-implemented method for training a recurrent neural network using forward propagation rather than back propagation through time. The method is particularly suited to training sparse recurrent neural networks, and may be implemented on specialized hardware.

公开(公告)号：US11069345B2

公开(公告)日：2021-07-20

申请号：US16719424

申请日：2019-12-18

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: G10L15/16 ,  G06N3/04 ,  G06N3/08 ,  G10L15/02 ,  G10L15/22

Abstract: Methods, systems, and apparatus, including computer programs encoded on computer storage media, for performing speech recognition by generating a neural network output from an audio data input sequence, where the neural network output characterizes words spoken in the audio data input sequence. One of the methods includes, for each of the audio data inputs, providing a current audio data input sequence that comprises the audio data input and the audio data inputs preceding the audio data input in the audio data 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 audio data inputs: receive the current audio data input sequence for the audio data input, and process the current audio data input sequence to generate an alternative representation for the audio data input.

公开(公告)号：US20210089909A1

公开(公告)日：2021-03-25

申请号：US17032578

申请日：2020-09-25

Applicant: DeepMind Technologies Limited

Inventor： Mikolaj Binkowski ,  Karen Simonyan ,  Jeffrey Donahue ,  Aidan Clark ,  Sander Etienne Lea Dieleman ,  Erich Konrad Elsen ,  Luis Carlos Cobo Rus ,  Norman Casagrande

IPC: G06N3/08 ,  G06N3/04 ,  G06K9/62

Abstract: Methods, systems, and apparatus, including computer programs encoded on computer storage media, for generating output audio examples using a generative neural network. One of the methods includes obtaining a training conditioning text input; processing a training generative input comprising the training conditioning text input using a feedforward generative neural network to generate a training audio output; processing the training audio output using each of a plurality of discriminators, wherein the plurality of discriminators comprises one or more conditional discriminators and one or more unconditional discriminators; determining a first combined prediction by combining the respective predictions of the plurality of discriminators; and determining an update to current values of a plurality of generative parameters of the feedforward generative neural network to increase a first error in the first combined prediction.

公开(公告)号：US20210034909A1

公开(公告)日：2021-02-04

申请号：US16995307

申请日：2020-08-17

Applicant: DeepMind Technologies Limited

Inventor： Maxwell Elliot Jaderberg ,  Karen Simonyan ,  Andrew Zisserman ,  Koray Kavukcuoglu

IPC: G06K9/52 ,  G06N3/04 ,  G06K9/46 ,  G06N3/08 ,  G06K9/03

Abstract: Methods, systems, and apparatus, including computer programs encoded on computer storage media, for processing inputs using an image processing neural network system that includes a spatial transformer module. One of the methods includes receiving an input feature map derived from the one or more input images, and applying a spatial transformation to the input feature map to generate a transformed feature map, comprising: processing the input feature map to generate spatial transformation parameters for the spatial transformation, and sampling from the input feature map in accordance with the spatial transformation parameters to generate the transformed feature map.

公开(公告)号：US10586531B2

公开(公告)日：2020-03-10

申请号：US16209661

申请日：2018-12-04

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: G10L15/16 ,  G06N3/04 ,  G10L15/02 ,  G10L15/22 ,  G06N3/08

Abstract: Methods, systems, and apparatus, including computer programs encoded on computer storage media, for performing speech recognition by generating a neural network output from an audio data input sequence, where the neural network output characterizes words spoken in the audio data input sequence. One of the methods includes, for each of the audio data inputs, providing a current audio data input sequence that comprises the audio data input and the audio data inputs preceding the audio data input in the audio data 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 audio data inputs: receive the current audio data input sequence for the audio data input, and process the current audio data input sequence to generate an alternative representation for the audio data input.

公开(公告)号：US10402700B2

公开(公告)日：2019-09-03

申请号：US15721089

申请日：2017-09-29

Applicant: DeepMind Technologies Limited

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

IPC: G06K9/66 ,  H04N19/50 ,  H04N19/52 ,  G06N3/04 ,  G06N3/08 ,  G06K9/46 ,  G06K9/62 ,  H04N19/186 ,  H04N19/172 ,  H04N19/182

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：US20180330185A1

公开(公告)日：2018-11-15

申请号：US16041567

申请日：2018-07-20

Applicant: DeepMind Technologies Limited

Inventor： Maxwell Elliot Jaderberg ,  Karen Simonyan ,  Andrew Zisserman ,  Koray Kavukcuoglu

IPC: G06K9/52 ,  G06N3/08 ,  G06K9/46 ,  G06K9/03 ,  G06N3/04

Abstract: Methods, systems, and apparatus, including computer programs encoded on computer storage media, for processing inputs using an image processing neural network system that includes a spatial transformer module. One of the methods includes receiving an input feature map derived from the one or more input images, and applying a spatial transformation to the input feature map to generate a transformed feature map, comprising: processing the input feature map to generate spatial transformation parameters for the spatial transformation, and sampling from the input feature map in accordance with the spatial transformation parameters to generate the transformed feature map.

公开(公告)号：US20250148282A1

公开(公告)日：2025-05-08

申请号：US18919108

申请日：2024-10-17

Applicant: DeepMind Technologies Limited

Inventor： Karen Simonyan ,  David Silver ,  Julian Schrittwieser

IPC: G06N3/08 ,  G06N7/01

Abstract: Methods, systems and apparatus, including computer programs encoded on computer storage media, for training an action selection neural network. One of the methods includes receiving an observation characterizing a current state of the environment; determining a target network output for the observation by performing a look ahead search of possible future states of the environment starting from the current state until the environment reaches a possible future state that satisfies one or more termination criteria, wherein the look ahead search is guided by the neural network in accordance with current values of the network parameters; selecting an action to be performed by the agent in response to the observation using the target network output generated by performing the look ahead search; and storing, in an exploration history data store, the target network output in association with the observation for use in updating the current values of the network parameters.