Black-box variational inference, example with linear models

Motivation

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.

Dependencies

You will need python 3 with autograd, matplotlib, and scipy.

Demo

See also

• 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.

Authors

Laurent de Vito

License

All third-party libraries are subject to their own license.

This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.