Sum-product networks: A survey

R Sánchez-Cauce, I París… - IEEE Transactions on …, 2021 - ieeexplore.ieee.org
A sum-product network (SPN) is a probabilistic model, based on a rooted acyclic directed
graph, in which terminal nodes represent probability distributions and non-terminal nodes …

On relaxing determinism in arithmetic circuits

A Choi, A Darwiche - International Conference on Machine …, 2017 - proceedings.mlr.press
The past decade has seen a significant interest in learning tractable probabilistic
representations. Arithmetic circuits (ACs) were among the first proposed tractable …

Visualizing and understanding sum-product networks

A Vergari, N Di Mauro, F Esposito - Machine Learning, 2019 - Springer
Abstract Sum-Product Networks (SPNs) are deep tractable probabilistic models by which
several kinds of inference queries can be answered exactly and in a tractable time. They …

Deep convolutional sum-product networks

CJ Butz, JS Oliveira, AE dos Santos… - Proceedings of the AAAI …, 2019 - ojs.aaai.org
We give conditions under which convolutional neural networks (CNNs) define valid sum-
product networks (SPNs). One subclass, called convolutional SPNs (CSPNs), can be …

Solving marginal map exactly by probabilistic circuit transformations

YJ Choi, T Friedman… - … Conference on Artificial …, 2022 - proceedings.mlr.press
Probabilistic circuits (PCs) are a class of tractable probabilistic models that allow efficient,
often linear-time, inference of queries such as marginals and most probable explanations …

Lightweight Materialization for Fast Dashboards Over Joins

Z Huang, E Wu - Proceedings of the ACM on Management of Data, 2023 - dl.acm.org
Dashboards are vital in modern business intelligence tools, providing non-technical users
with an interface to access comprehensive business data. With the rise of cloud technology …

Maximum a posteriori inference in sum-product networks

J Mei, Y Jiang, K Tu - Proceedings of the AAAI Conference on Artificial …, 2018 - ojs.aaai.org
Sum-product networks (SPNs) are a class of probabilistic graphical models that allow
tractable marginal inference. However, the maximum a posteriori (MAP) inference in SPNs is …

Tractable Boolean and arithmetic circuits

A Darwiche - Neuro-Symbolic Artificial Intelligence: The State of …, 2021 - ebooks.iospress.nl
Tractable Boolean and arithmetic circuits have been studied extensively in AI for over two
decades now. These circuits were initially proposed as “compiled objects,” meant to facilitate …

[HTML][HTML] Robustifying sum-product networks

DD Mauá, D Conaty, FG Cozman… - International Journal of …, 2018 - Elsevier
Sum-product networks are a relatively new and increasingly popular family of probabilistic
graphical models that allow for marginal inference with polynomial effort. They have been …

Restructuring tractable probabilistic circuits

H Zhang, B Wang, M Arenas, GV Broeck - arXiv preprint arXiv:2411.12256, 2024 - arxiv.org
Probabilistic circuits (PCs) is a unifying representation for probabilistic models that support
tractable inference. Numerous applications of PCs like controllable text generation depend …