Batch Normalization: Accelerating Deep Network Training byReducing Internal Covariate Shift论文学习
Batch Normalization: Accelerating Deep Network Training byReducing Internal Covariate Shift 文章试图解决的问题 内部协变量转移(internal covariate shift)：在训练进行时，网络中的参数不断改变，导致每一层的输入分配会进行变化，这个现象被称作内部协变量转移 由于分布变化，所以需要更小的学
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相关文章
- 1. Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift 论文解读
- 2. Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift 论文翻译（转）
- 3. 《Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift》论文笔记
- 4. 论文阅读 Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift
- 5. 论文笔记：Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift
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- 9. Batch Normalization: Accelerating Deep Network Training b y Reducing Internal Covariate Shift
- 10. 【inv2】Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift