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20212026
most citedBlack-Box Quantum State Preparation with Inverse Coefficients

9 citations · 14 across the 7 of their papers we have counts for

collaborators

7 papers

quant-ph2026

Defeating Barren Plateaus with Task-Aligned Symmetry

Ruipeng Xing, Yanan Li, Zhen Shang +3

Barren plateaus -- the exponential vanishing of gradients -- are a fundamental obstacle to training scalable quantum neural networks. Whether they arise in quantum recurrent neural…

eess.SY2023★ 1 cited

Real-Time Progressive Learning: Accumulate Knowledge from Control with Neural-Network-Based Selective Memory

Yiming Fei, Jiangang Li, Yanan Li

Memory, as the basis of learning, determines the storage, update and forgetting of knowledge and further determines the efficiency of learning. Featured with the mechanism of memor…

quant-ph2023★ 3 cited

A natural NISQ model of quantum self-attention mechanism

Shangshang Shi, Zhimin Wang, Jiaxin Li +5

The self-attention mechanism (SAM) has demonstrated remarkable success in various applications. However, training SAM on classical computers becomes computationally challenging as…

quant-ph2023

Hybrid quantum-classical convolutional neural network for phytoplankton classification

Shangshang Shi, Zhimin Wang, Ruimin Shang +4

The taxonomic composition and abundance of phytoplankton, having direct impact on marine ecosystem dynamic and global environment change, are listed as essential ocean variables. P…

quant-ph2023★ 1 cited

Quantum Recurrent Neural Networks for Sequential Learning

Yanan Li, Zhimin Wang, Rongbing Han +6

Quantum neural network (QNN) is one of the promising directions where the near-term noisy intermediate-scale quantum (NISQ) devices could find advantageous applications against cla…

eess.SY2022

Selective Memory Recursive Least Squares: Recast Forgetting into Memory in RBF Neural Network Based Real-Time Learning

Yiming Fei, Jiangang Li, Yanan Li

In radial basis function neural network (RBFNN) based real-time learning tasks, forgetting mechanisms are widely used such that the neural network can keep its sensitivity to new d…

quant-ph2021★ 9 cited

Black-Box Quantum State Preparation with Inverse Coefficients

Shengbin Wang, Zhimin Wang, Runhong He +8

Black-box quantum state preparation is a fundamental building block for many higher-level quantum algorithms, which is applied to transduce the data from computational basis into a…