3 papers
cond-mat.stat-mech2026
Branch-and-Bound Tensor Networks for Exact Ground-State Characterization
Yijia Wang, Xuanzhao Gao, Pan Zhang +2
Characterizing the ground-state properties of disordered systems, such as spin glasses and combinatorial optimization problems, is fundamental to science and engineering. However,…
math.OC2024
Automated Discovery of Branching Rules with Optimal Complexity for the Maximum Independent Set Problem
Xuan-Zhao Gao, Yi-Jia Wang, Pan Zhang +1
The branching algorithm is a fundamental technique for designing fast exponential-time algorithms to solve combinatorial optimization problems exactly. It divides the entire soluti…
cs.LG2024
Probabilistic Inference in the Era of Tensor Networks and Differential Programming
Martin Roa-Villescas, Xuanzhao Gao, Sander Stuijk +2
Probabilistic inference is a fundamental task in modern machine learning. Recent advances in tensor network (TN) contraction algorithms have enabled the development of better exact…