Invention Grant
- Patent Title: Memory augmented generative temporal models
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Application No.: US17113669Application Date: 2020-12-07
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Publication No.: US11977967B2Publication Date: 2024-05-07
- Inventor: Gregory Duncan Wayne , Chia-Chun Hung , Mevlana Celaleddin Gemici , Adam Anthony Santoro
- Applicant: DeepMind Technologies Limited
- Applicant Address: GB London
- Assignee: DeepMind Technologies Limited
- Current Assignee: DeepMind Technologies Limited
- Current Assignee Address: GB London
- Agency: Fish & Richardson P.C.
- Main IPC: G06N3/06
- IPC: G06N3/06 ; G06N3/0455 ; G06N3/049 ; G06N20/00 ; G06F16/908 ; G06N3/084

Abstract:
Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for generating sequences of predicted observations, for example images. In one aspect, a system comprises a controller recurrent neural network, and a decoder neural network to process a set of latent variables to generate an observation. An external memory and a memory interface subsystem is configured to, for each of a plurality of time steps, receive an updated hidden state from the controller, generate a memory context vector by reading data from the external memory using the updated hidden state, determine a set of latent variables from the memory context vector, generate a predicted observation by providing the set of latent variables to the decoder neural network, write data to the external memory using the latent variables, the updated hidden state, or both, and generate a controller input for a subsequent time step from the latent variables.
Public/Granted literature
- US20210089968A1 MEMORY AUGMENTED GENERATIVE TEMPORAL MODELS Public/Granted day:2021-03-25
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