graphdatascience is a Python client for operating and working with the Neo4j Graph Data Science (GDS) library. It enables users to write pure Python code to project graphs, run algorithms, as well as ...

This library is not meant to stand-alone. Instead it defines common helpers used by all Google API clients. For more information, see the documentation. Python == 2.7, Python == 3.5, Python == 3.6, ...

Abstract: Bayesian inference provides a methodology for parameter estimation and uncertainty quantification in machine learning and deep learning methods. Variational inference and Markov Chain ...

Abstract: Call graphs play an important role in different contexts, such as profiling and vulnerability propagation analysis. Generating call graphs in an efficient manner can be a challenging task ...