InferPy: Deep Probabilistic Modeling with Tensorflow Made Easy


InferPy is a high-level API for probabilistic modeling with deep neural networks written in Python and capable of running on top of Tensorflow. InferPy’s API is strongly inspired by Keras and it has a focus on enabling flexible data processing, easy-to-code probabilistic modeling, scalable inference, and robust model validation.

Use InferPy if you need a probabilistic programming language that:

  • Allows easy and fast prototyping of hierarchical probabilistic models with a simple and user-friendly API inspired by Keras.

  • Automatically creates computational efficient batched models without the need to deal with complex tensor operations and theoretical concepts.

  • Run seamlessly on CPU and GPU by relying on Tensorflow, without having to learn how to use Tensorflow.

  • Defines probabilistic models with complex probabilistic constructs containing deep neural networks.

A set of examples can be found in the Probabilistic Model Zoo section.