Aboleth — A TensorFlow Framework for Bayesian Deep Learning

Aboleth - A TensorFlow Framework for Bayesian Deep Learning

Depiction of a Bayesian Neural Net that is easily constructed using Aboleth.

I am one of the primary creators of Aboleth, a bare-bones TensorFlow framework for Bayesian deep learning and Gaussian process approximation.

The purpose of Aboleth is to provide a set of high performance and light weight components for building Bayesian neural nets and approximate (deep) Gaussian process computational graphs. We aim for minimal abstraction over pure TensorFlow, so you can still assign parts of the computational graph to different hardware, use your own data feeds/queues, and manage your own sessions etc.

The project page is on github.