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20202026
most citedProvable Tensor-Train Format Tensor Completion by Riemannian Optimization

15 citations · 29 across the 13 of their papers we have counts for

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2 papers · 1 filter

quant-ph2026

Online Riemannian Gradient Descent for Quantum State Tomography with Matrix Product Operators

Jian-Feng Cai, Jingyang Li, Xiaoqun Zhang +1

Matrix product operators (MPOs) provide a scalable approach for quantum state tomography (QST) by offering a compact representation of many-body mixed states with limited entanglem…

stat.ME2026

Uncertainty Quantification for Noisy Low-tubal-rank Tensor Completion

Jiuqian Shang, Jingyang Li, Yang Chen

High-dimensional tensor data often exhibit strong temporal correlations that appear as low-dimensional structures in the frequency domain. While the low-tubal-rank tensor model eff…