Machine learning methods in solving the boolean satisfiability problem

W Guo, HL Zhen, X Li, W Luo, M Yuan, Y **… - Machine Intelligence …, 2023 - Springer
This paper reviews the recent literature on solving the Boolean satisfiability problem (SAT),
an archetypal NP-complete problem, with the aid of machine learning (ML) techniques. Over …

A systematic survey on deep generative models for graph generation

X Guo, L Zhao - IEEE Transactions on Pattern Analysis and …, 2022 - ieeexplore.ieee.org
Graphs are important data representations for describing objects and their relationships,
which appear in a wide diversity of real-world scenarios. As one of a critical problem in this …

Hardsatgen: Understanding the difficulty of hard sat formula generation and a strong structure-hardness-aware baseline

Y Li, X Chen, W Guo, X Li, W Luo, J Huang… - Proceedings of the 29th …, 2023 - dl.acm.org
Industrial SAT formula generation is a critical yet challenging task. Existing SAT generation
approaches can hardly simultaneously capture the global structural properties and maintain …

G2sat: Learning to generate sat formulas

J You, H Wu, C Barrett… - Advances in neural …, 2019 - proceedings.neurips.cc
Abstract The Boolean Satisfiability (SAT) problem is the canonical NP-complete problem
and is fundamental to computer science, with a wide array of applications in planning …

On the performance of deep generative models of realistic sat instances

I Garzón, P Mesejo, J Giráldez-Cru - … International Conference on …, 2022 - drops.dagstuhl.de
Generating realistic random SAT instances-random SAT formulas with computational
characteristics similar to the ones of application SAT benchmarks-is a challenging problem …

Graph neural network based time estimator for SAT solver

J Liu, W **ao, H Cheng, C Shi - International Journal of Machine Learning …, 2024 - Springer
SAT-based formal verification is a systematic process to prove the correctness of computer
hardware design based on formal specifications, providing an alternative to time-consuming …

Neural fault analysis for sat-based atpg

J Huang, HL Zhen, N Wang, H Mao… - 2022 IEEE …, 2022 - ieeexplore.ieee.org
Continued advances in process technology have led to a relentless increase in the design
complexity of integrated circuits (ICs). In order to meet the increasing demand of low …

W2SAT: Learning to generate SAT instances from Weighted Literal Incidence Graphs

W Wen, T Yu - arxiv preprint arxiv:2302.00272, 2023 - arxiv.org
The Boolean Satisfiability (SAT) problem stands out as an attractive NP-complete problem in
theoretic computer science and plays a central role in a broad spectrum of computing …

HardCore Generation: Generating Hard UNSAT Problems for Data Augmentation

J Cotnareanu, Z Zhang, HL Zhen, Y Zhang… - arxiv preprint arxiv …, 2024 - arxiv.org
Efficiently determining the satisfiability of a boolean equation--known as the SAT problem for
brevity--is crucial in various industrial problems. Recently, the advent of deep learning …

[PDF][PDF] Lightweight Online Learning for Sets of Related Problems in Automated Reasoning

H Wu, C Hahn, F Lonsing, M Mann… - 2023 Formal Methods …, 2023 - library.oapen.org
We present Self-Driven Strategy Learning (SDSL), a lightweight online learning
methodology for automated reasoning tasks that involve solving a set of related problems …