Practical experiences using ADVI training Bayesian neural network


I am just simply using KLqp, and my neural network model is very simple so it would be using the reparameteric gradient, which is the ADVI algorithm in the ADVI paper.

I have found that

  • using Adam optimizer is really helpful especially in training neural networks
  • using batch training is helpful
  • number of samples doesn’t matter a lot

Please comment below if you find other things helpful!


Can I ask how you got that working? I’m a tensorflow beginner and is trying to figure out how to implement a neural network for CIFAR10 with KLqp. However, my model currently won’t train properly and I’m unsure how to debug it.



I think try to fully understand this tutorial is the way to go:

Hope this helps!

I found initialization with MAP solution is extremely helpful for dealing with very large neural network models.

I also found the get_parents and get_variable method in RandomVariable class is very helpful in debugging process.

老铁,你有evaluate(‘binary_accuracy’) 或者 'categoriate_accuracy’吗?可否看下你这个的代码?如果可以的话,麻烦大侠 发给我的邮箱可否?(邮箱