InferPy: Probabilistic Modeling with Deep Neural Networks Made Easy

Autor:	Cózar, Javier, Cabañas, Rafael, Salmerón, Antonio, Masegosa, Andrés R.
Rok vydání:	2019
Předmět:	Computer Science - Machine Learning Statistics - Machine Learning
Druh dokumentu:	Working Paper
Popis:	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. Comment: 5 pages limit (paper submitted to an original software publication track). This paper briefly describes a scientific software
Databáze:	arXiv
Externí odkaz:	http://arxiv.org/abs/1908.11161 Zobrazit plný text záznamu View this record from Arxiv