
基本信息:
- 专利标题: SIMPLIFICATION OF NEURAL NETWORK MODELS
- 申请号:US17658462 申请日:2022-04-08
- 公开(公告)号:US20220230052A1 公开(公告)日:2022-07-21
- 发明人: Henry Markram , Wulfram Gerstner , Marc-Oliver Gewaltig , Christian Rössert , Eilif Benjamin Muller , Christian Pozzorini , Idan Segev , James Gonzalo King , Csaba Erö , Willem Wybo
- 申请人: Ecole Polytechnique Federale De Lausanne (EPFL)
- 申请人地址: CH Lausanne
- 专利权人: Ecole Polytechnique Federale De Lausanne (EPFL)
- 当前专利权人: Ecole Polytechnique Federale De Lausanne (EPFL)
- 当前专利权人地址: CH Lausanne
- 主分类号: G06N3/04
- IPC分类号: G06N3/04 ; G06N3/08
摘要:
The simplification of neural network models is described. For example, a method for simplifying a neural network model includes providing the neural network model to be simplified, defining a first temporal filter for the conveyance of input from a neuron to an other spatially-extended neuron along the arborized projection, defining a second temporal filter for the conveyance of input from yet another neuron to the spatially-extended neuron along the arborized projection, replacing, in the neural network model, the first, spatially-extended neuron with a first, spatially-constrained neuron and the arborized projection with a first connection extending between the first, spatially-constrained neuron and the second neuron, wherein the first connection filters input from the second neuron in accordance with the first temporal filter and a second connection extending between the first spatially-constrained neuron and the third neuron.
公开/授权文献:
- US11983620B2 Simplification of spiking neural network models 公开/授权日:2024-05-14
IPC结构图谱:
G | 物理 |
--G06 | 计算;推算;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 |
--------G06N3/02 | .采用神经网络模型 |
----------G06N3/04 | ..体系结构,例如,互连拓扑 |