Duvenaud showed in Black-Box Stochastic Variational Inference in Five Lines of Python how to make use of the Python module autograd to easily code black-box variational inference introduced in Black Box Variational Inference by Ranganath et al.
I adapted his code to linear models.
You will need python 3 with autograd, matplotlib, and scipy.
- Vprop: Variational Inference using RMSprop by Khan et al.:
As in this paper, I deliberately chose a prior of the form
so that results can be compared to those obtained using the algorithm Vprop. - Automatic Variational Inference in Stan by Kucukelbir et al.: They automated black-box variational inference. What is great is that you can constraint the support of a random variable.
Laurent de Vito
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