InferPy: Probabilistic Modelling with Tensorflow Made Easy

InferPy is a high-level API for probabilistic modeling 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 probablistic modelling, 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.
• Run seamlessly on CPU and GPU by relying on Tensorflow, without having to learn how to use Tensorflow.

Quick Start

• Getting Started:
• Guiding Principles

Guides

• Guide to Building Probabilistic Models
• Guide to Approximate Inference
• Guide to Model Validation
• Guide to Data Handling

Model Zoo

• Probabilistic Model Zoo

Package Reference

• inferpy package
• inferpy.models package