Fast and Separable Estimation in High-Dimensional Tensor Gaussian Graphical Models
Sign Up to like & getrecommendations! Published in 2021 at "Journal of Computational and Graphical Statistics"
DOI: 10.1080/10618600.2021.1938086
Abstract: In the tensor data analysis, the Kronecker covariance structure plays a vital role in unsupervised learning and regression. Under the Kronecker covariance model assumption, the covariance of an M -way tensor is parameterized as the… read more here.
Keywords: high dimensional; estimation; dimensional tensor; tensor ... See more keywords
On two-dimensional tensor network group symmetries
Sign Up to like & getrecommendations! Published in 2025 at "New Journal of Physics"
DOI: 10.1088/1367-2630/ae124f
Abstract: We introduce two-dimensional tensor-network representations of finite groups carrying a 4-cocycle index. We characterize the associated gapped (2+1)D phases that emerge when these anomalous symmetries act on tensor-network ground states. We further develop related tensor-network… read more here.
Keywords: dimensional tensor; tensor; tensor network; two dimensional ... See more keywords
Efficient calculation of three-dimensional tensor networks
Sign Up to like & getrecommendations! Published in 2022 at "Physical Review B"
DOI: 10.1103/physrevb.107.165127
Abstract: We have proposed an efficient algorithm to calculate physical quantities in the translational invariant three-dimensional tensor networks, which is particularly relevant to the study of the three-dimensional classical statistical models and the (2+1)-dimensional quantum lattice… read more here.
Keywords: efficient calculation; calculation three; tensor networks; dimensional tensor ... See more keywords