Sum-product networks: A survey

Understand

A sum-product network (SPN) is a probabilistic model, based on a rooted acyclic directed graph, in which terminal nodes represent univariate probability distributions and non-terminal nodes represent convex combinations (weighted sums) and products of probability functions.

• They are closely related to probabilistic graphical models, in particular to Bayesian networks with multiple context-specific independencies.
• Their main advantage is the possibility of building tractable models from data, i.e., models that can perform several inference tasks in time proportional to the number of links in the graph.
• They are somewhat similar to neural networks and can address the same kinds of problems, such as image processing and natural language understanding.