Tars
Tars is a deep generative models library. It has the following features:

Various distributions
 Gaussian, Bernoulli, Laplace, Gamma, Beta, Dirichlet, Bernoulli, Categorical, and so on.
 Hierarchical latent distributions (New!).
 We can draw samples from these distributions by the reparameterization trick .

Various models

Various lower bounds
 The evidence lower bound (ELBO, which is the same as the original lower bound)
 The importance sampling lower bound
 The variational R'enyi bound

Note: Some of the implementations of the above models have not yet been released in this version. If you want to use such models, please use the old version (v0.0.2).

For a more detailed explanation of this library, please refer to this page (in Japanese).
Installation
$ git clone https://github.com/masasu/Tars.git
$ pip install e Tars processdependencylinks
or
$ pip install e git://github.com/masasu/Tars processdependencylinks
When you execute this command, the following packages will be automatically installed in your environment:
 Theano
 Lasagne
 progressbar2
 matplotlib
 sklearn
Examples
Please go to the examples directory and try to run some examples.