Invention Grant
- Patent Title: Gated linear networks
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Application No.: US16759993Application Date: 2018-11-30
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Publication No.: US11842264B2Publication Date: 2023-12-12
- Inventor: Agnieszka Grabska-Barwinska , Peter Toth , Christopher Mattern , Avishkar Bhoopchand , Tor Lattimore , Joel William Veness
- 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.
- International Application: PCT/EP2018/083094 2018.11.30
- International Announcement: WO2019/106132A 2019.06.06
- Date entered country: 2020-04-28
- Main IPC: G06N3/063
- IPC: G06N3/063 ; G06N3/047 ; G06N3/048 ; G06N7/01

Abstract:
Methods, systems, and apparatus, including computer programs encoded on computer storage media, for a neural network system comprising one or more gated linear networks. A system includes: one or more gated linear networks, wherein each gated linear network corresponds to a respective data value in an output data sample and is configured to generate a network probability output that defines a probability distribution over possible values for the corresponding data value, wherein each gated linear network comprises a plurality of layers, wherein the plurality of layers comprises a plurality of gated linear layers, wherein each gated linear layer has one or more nodes, and wherein each node is configured to: receive a plurality of inputs, receive side information for the node; combine the plurality of inputs according to a set of weights defined by the side information, and generate and output a node probability output for the corresponding data value.
Public/Granted literature
- US20200349418A1 GATED LINEAR NETWORKS Public/Granted day:2020-11-05
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