4 papers
Plastic tensor networks for interpretable generative modeling
Katsuya O. Akamatsu, Kenji Harada, Tsuyoshi Okubo +1
A structural optimization scheme for a single-layer nonnegative adaptive tensor tree (NATT) that models a target probability distribution is proposed as an alternative paradigm for…
Tensor tree learns hidden relational structures in data to construct generative models
Kenji Harada, Tsuyoshi Okubo, Naoki Kawashima
Based on the tensor tree network with the Born machine framework, we propose a general method for constructing a generative model by expressing the target distribution function as…
TeNeS-v2: Enhancement for Real-Time and Finite Temperature Simulations of Quantum Many-Body Systems
Yuichi Motoyama, Tsuyoshi Okubo, Kazuyoshi Yoshimi +4
Quantum many-body systems are challenging targets for computational physics due to their large degrees of freedom. The tensor networks, particularly Tensor Product States (TPS) and…
Nuclear norm regularized loop optimization for tensor network
Kenji Homma, Tsuyoshi Okubo, Naoki Kawashima
We propose a loop optimization algorithm based on nuclear norm regularization for tensor network. The key ingredient of this scheme is to introduce a rank penalty term proposed in…