论文标题
神经网络量词田间理论对应关系的重归其化
Renormalization in the neural network-quantum field theory correspondence
论文作者
论文摘要
可以用量子场理论（NN-QFT对应关系）来描述神经网络的统计合奏。无限宽度限制映射到自由场理论，而有限的N校正映射到相互作用。在审查了对应关系之后，我们将描述如何在这种情况下实施重新归一化，并讨论翻译不变核的初步数值结果。一个主要的结果是，改变神经网络重量分布的标准偏差对应于网络空间中的重新归一化流。
A statistical ensemble of neural networks can be described in terms of a quantum field theory (NN-QFT correspondence). The infinite-width limit is mapped to a free field theory, while finite N corrections are mapped to interactions. After reviewing the correspondence, we will describe how to implement renormalization in this context and discuss preliminary numerical results for translation-invariant kernels. A major outcome is that changing the standard deviation of the neural network weight distribution corresponds to a renormalization flow in the space of networks.
