6 citations · 9 across the 4 of their papers we have counts for
5 papers · 1 filter
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,…
Tensor Network Message Passing
Yijia Wang, Yuwen Ebony Zhang, Feng Pan +1
When studying interacting systems, computing their statistical properties is a fundamental problem in various fields such as physics, applied mathematics, and machine learning. How…
Tensor networks for unsupervised machine learning
Jing Liu, Sujie Li, Jiang Zhang +1
Modeling the joint distribution of high-dimensional data is a central task in unsupervised machine learning. In recent years, many interests have been attracted to developing learn…
Boltzmann machines as two-dimensional tensor networks
Sujie Li, Feng Pan, Pengfei Zhou +1
Restricted Boltzmann machines (RBM) and deep Boltzmann machines (DBM) are important models in machine learning, and recently found numerous applications in quantum many-body physic…
Phase transitions and optimal algorithms for semi-supervised classifications on graphs: from belief propagation to graph convolution network
Pengfei Zhou, Tianyi Li, Pan Zhang
We perform theoretical and algorithmic studies for the problem of clustering and semi-supervised classification on graphs with both pairwise relational information and single-point…