- Patent Title: Neural architecture search based on synaptic connectivity graphs
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Application No.: US16776108Application Date: 2020-01-29
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Publication No.: US11620487B2Publication Date: 2023-04-04
- Inventor: Sarah Ann Laszlo , Philip Edwin Watson , Georgios Evangelopoulos
- Applicant: X Development LLC
- Applicant Address: US CA Mountain View
- Assignee: X Development LLC
- Current Assignee: X Development LLC
- Current Assignee Address: US CA Mountain View
- Agency: Fish & Richardson P.C.
- Priority: GR20190100588 20191231
- Main IPC: G06N3/04
- IPC: G06N3/04 ; G06N3/006 ; G06N3/08 ; G06K9/62 ; G10L25/30 ; G10L25/51 ; G06V10/426

Abstract:
Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for selecting a neural network architecture for performing a machine learning task. In one aspect, a method comprises: obtaining data defining a synaptic connectivity graph representing synaptic connectivity between neurons in a brain of a biological organism; generating data defining a plurality of candidate graphs based on the synaptic connectivity graph; determining, for each candidate graph, a performance measure on a machine learning task of a neural network having a neural network architecture that is specified by the candidate graph; and selecting a final neural network architecture for performing the machine learning task based on the performance measures.
Public/Granted literature
- US20210201107A1 NEURAL ARCHITECTURE SEARCH BASED ON SYNAPTIC CONNECTIVITY GRAPHS Public/Granted day:2021-07-01
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