- 专利标题: NEURAL ARCHITECTURE SEARCH BASED ON SYNAPTIC CONNECTIVITY GRAPHS
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申请号: US16776108申请日: 2020-01-29
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公开(公告)号: US20210201107A1公开(公告)日: 2021-07-01
- 发明人: Sarah Ann Laszlo , Philip Edwin Watson , Georgios Evangelopoulos
- 申请人: X Development LLC
- 申请人地址: US CA Mountain View
- 专利权人: X Development LLC
- 当前专利权人: X Development LLC
- 当前专利权人地址: US CA Mountain View
- 优先权: GR20190100588 20191231
- 主分类号: G06N3/00
- IPC分类号: G06N3/00 ; G06N3/04 ; G06N3/08 ; G06K9/62 ; G06K9/46 ; G10L25/51 ; G10L25/30
摘要:
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.
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IPC分类:
G | 物理 |
G06 | 计算;推算或计数 |
G06N | 基于特定计算模型的计算机系统 |
G06N3/00 | 基于生物学模型的计算机系统 |