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If you consider the central limit theorem, input data will follow a normal distribution with a constant mean. Thus, if the input data are normalized, the mean will close to 0. So padding with 0 (the mean) doesn't affect the distribution. I have done some testings in my research, which show the output of batch normalization will follow normal distributions with the mean close to 0. Also if you know the convolution operation in the traditional signal processing, you can find that zero padding is just the standardized way.

If you consider the central limit theorem, input data will follow a normal distribution with a constant mean. Thus, if the input data are normalized, the mean will be close to 0. So padding with 0 (the mean) doesn't affect the distribution. I have done some testings in my research, which show the output of batch normalization will follow normal distributions with the mean close to 0. Also if you know the convolution operation in traditional signal processing, you can find that zero padding is just the standardized way.

If you consider the central limit theorem, input data will follow a normal distribution with a constant mean. Thus, if the input data are normalized, the mean will close to 0. So padding with 0 (the mean) doesn't affect the distribution. I have done some testings in my research, which show the output of batch normalization will follow normal distributions with the mean close to 0.

If you consider the central limit theorem, input data will follow a normal distribution with a constant mean. Thus, if the input data are normalized, the mean will close to 0. So padding with 0 (the mean) doesn't affect the distribution. I have done some testings in my research, which show the output of batch normalization will follow normal distributions with the mean close to 0. Also if you know the convolution operation in the traditional signal processing, you can find that zero padding is just the standardized way.

If you consider the central limit theorem, input data will follow a normal distribution with a constant mean. Thus, if the input data are normalized, the mean will close to 0. So padding with 0 (the mean) doesn't affect the distribution.

If you consider the central limit theorem, input data will follow a normal distribution with a constant mean. Thus, if the input data are normalized, the mean will close to 0. So padding with 0 (the mean) doesn't affect the distribution. I have done some testings in my research, which show the output of batch normalization will follow normal distributions with the mean close to 0.