Contextual Graph Markov Model A Deep And Generative Approach To Graph Processing

# Contextual Graph Markov Model: A Deep and Generative Approach to Graph Processing

**arXiv ID:** 1805.10636
**Authors:** Davide Bacciu, Federico Errica, Alessio Micheli
**Published:** 2018-05-27T15:04:05Z
**Abstract:**
We introduce the Contextual Graph Markov Model, an approach combining ideas from generative models and neural networks for the processing of graph data. It founds on a constructive methodology to build a deep architecture comprising layers of probabilistic models that learn to encode the structured information in an incremental fashion. Context is diffused in an efficient and scalable way across the graph vertexes and edges. The resulting graph encoding is used in combination with discriminative models to address structure classification benchmarks.

## Skill Description

This skill is generated from the arXiv paper: Contextual Graph Markov Model: A Deep and Generative Approach to Graph Processing (1805.10636).

## How to Use

[To be filled in by the user or by future automation]

## References

- [arXiv:1805.10636](http://arxiv.org/abs/1805.10636v2)