InferPy: Probabilistic Modeling with Deep Neural Networks Made Easy
This tool addresses usability issues for researchers and practitioners working with probabilistic deep learning, though it is incremental as it builds on existing libraries.
The authors tackled the complexity of using probabilistic modeling with deep neural networks by developing InferPy, a Python package that simplifies the API for defining, learning, and evaluating hierarchical models, built on TensorFlow Probability and Keras.
InferPy is a Python package for probabilistic modeling with deep neural networks. It defines a user-friendly API that trades-off model complexity with ease of use, unlike other libraries whose focus is on dealing with very general probabilistic models at the cost of having a more complex API. In particular, this package allows to define, learn and evaluate general hierarchical probabilistic models containing deep neural networks in a compact and simple way. InferPy is built on top of Tensorflow Probability and Keras.