公开(公告)号：US12032523B2

公开(公告)日：2024-07-09

申请号：US16818895

申请日：2020-03-13

Applicant: DeepMind Technologies Limited

Inventor： Yan Wu ,  Timothy Paul Lillicrap ,  Mihaela Rosca

IPC: G06F16/174 ,  G06N3/045 ,  G06N3/08

CPC classification number: G06F16/1744 ,  G06N3/045 ,  G06N3/08

Abstract: Methods, systems, and apparatus, including computer programs encoded on computer storage media, for compressed sensing using neural networks. One of the methods includes receiving an input measurement of an input data item; for each of one or more optimization steps: processing a latent representation using a generator neural network to generate a candidate reconstructed data item, processing the candidate reconstructed data item using a measurement neural network to generate a measurement of the candidate reconstructed data item, and updating the latent representation to reduce an error between the measurement and the input measurement; and processing the latent representation after the one or more optimization steps using the generator neural network to generate a reconstruction of the input data item.

公开(公告)号：US20210383243A1

公开(公告)日：2021-12-09

申请号：US17337376

申请日：2021-06-02

Applicant: DeepMind Technologies Limited

Inventor： Chongli Qin ,  Yan Wu

IPC: G06N3/08 ,  G06N3/04

Abstract: The training of an adversarial model is performed by respective update operations at each of a set of successive time steps to minimize an objective function having a plurality of loss components. The update operation includes at least one intermediate step of using gradients of the loss components for current values of the numerical parameters to generate intermediate values for the numerical parameters. A different set of intermediate values for each of the numerical parameters may be generated in each intermediate step. The update operation further includes generating respective updates to the current values of each of the numerical parameters based on functions of the gradients of at least one of the loss components with respect to the respective numerical parameters. This is done both for the current values of the numerical parameters and for the intermediate values of the numerical parameters.

公开(公告)号：US20200293497A1

公开(公告)日：2020-09-17

申请号：US16818895

申请日：2020-03-13

Applicant: DeepMind Technologies Limited

Inventor： Yan Wu ,  Timothy Paul Lillicrap ,  Mihaela Rosca

IPC: G06F16/174 ,  G06N3/04 ,  G06N3/08

Abstract: Methods, systems, and apparatus, including computer programs encoded on computer storage media, for compressed sensing using neural networks. One of the methods includes receiving an input measurement of an input data item; for each of one or more optimization steps: processing a latent representation using a generator neural network to generate a candidate reconstructed data item, processing the candidate reconstructed data item using a measurement neural network to generate a measurement of the candidate reconstructed data item, and updating the latent representation to reduce an error between the measurement and the input measurement; and processing the latent representation after the one or more optimization steps using the generator neural network to generate a reconstruction of the input data item.