Does someone knows the difference between xavier_normal_ and kaiming_normal_?
Like title. Does someone knows the difference between xavier_normal_ and kaiming_normal_?  Only Xavier have an argument 'gain' more than kaiming?

Read the documentation:

xavier_normal_


  Fills the input Tensor with values according to the method described in “Understanding the difficulty of training deep feedforward neural networks” - Glorot, X. &amp; Bengio, Y. (2010), using a normal distribution.


kaiming_normal_


  Fills the input Tensor with values according to the method described in “Delving deep into rectifiers: Surpassing human-level performance on ImageNet classification” - He, K. et al. (2015), using a normal distribution.


The given equations are completely different. For more details you'll have to read those papers.
