总结：Different Methods for Weight Initialization in Deep Learning

最新推荐文章于 2025-03-11 22:53:05 发布

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tangwei2014

最新推荐文章于 2025-03-11 22:53:05 发布

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分类专栏： DeepLearning 文章标签：深度学习 deep learning 权重初始化 MSRA

本文链接：https://blog.youkuaiyun.com/tangwei2014/article/details/47091881

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本文总结了深度学习中权重初始化的三种方法：高斯初始化、Xavier初始化和MSRA初始化。高斯初始化是最常见的方法，Xavier初始化考虑了输入和输出节点数，而MSRA初始化针对极深的ReLU模型，有助于从头开始训练。

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这里总结了三种权重的初始化方法，前两种比较常见，后一种是最新的。为了表达顺畅（当时写给一个歪果仁看的），用了英文，欢迎补充和指正。

尊重原创，转载请注明：http://blog.youkuaiyun.com/tangwei2014

1. Gaussian

Weights are randomly drawn from Gaussian distributions with fixed mean (e.g., 0) and fixed standard deviation (e.g., 0.01).

This is the most common initialization method in deep learning.

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