2 citations · 3 across the 9 of their papers we have counts for
9 papers
PQFA: Parallel Quantum Feature Augmentation of Fused Representations for Multimodal Classification
Mingzhu Wang, Yun Shang
Most multimodal learning methods improve how heterogeneous representations are aligned and fused, while post-fusion enhancement remains less explored. We propose Parallel Quantum F…
Hybrid Vision Transformer and Quantum Convolutional Neural Network for Image Classification
Mingzhu Wang, Yun Shang
Quantum machine learning (QML) holds promise for computational advantage, yet progress on real-world tasks is hindered by classical preprocessing and noisy devices. We introduce Vi…
A hybrid quantum walk model unifying discrete and continuous quantum walks
Tianen Chen, Yun Shang
Quantum walks, both discrete and continuous, serve as fundamental tools in quantum information processing with diverse applications. This work introduces a hybrid quantum walk mode…
Distributed Quantum Neural Networks on Distributed Photonic Quantum Computing
Kuan-Cheng Chen, Chen-Yu Liu, Yu Shang +2
We introduce a distributed quantum-classical framework that synergizes photonic quantum neural networks (QNNs) with matrix-product-state (MPS) mapping to achieve parameter-efficien…
A quantum speedup algorithm for TSP based on quantum dynamic programming with very few qubits
Bai Xujun, Shang Yun
The Traveling Salesman Problem (TSP) is a classical NP-hard problem that plays a crucial role in combinatorial optimization. In this paper, we are interested in the quantum search…
Approximation Theory and Applications of Randomized Neural Networks for Solving High-Dimensional PDEs
T. De Ryck, S. Mishra, Y. Shang +1
We present approximation results and numerical experiments for the use of randomized neural networks within physics-informed extreme learning machines to efficiently solve high-dim…
Entanglement distribution based on quantum walk in arbitrary quantum networks
Tianen Chen, Yun Shang, Chitong Chen +1
In large-scale quantum networks, quantum repeaters provide an efficient method to distribute entangled states among selected nodes for realizing long-distance and complicated quant…
Towards Biologically Plausible Computing: A Comprehensive Comparison
Changze Lv, Yufei Gu, Zhengkang Guo +16
Backpropagation is a cornerstone algorithm in training neural networks for supervised learning, which uses a gradient descent method to update network weights by minimizing the dis…
Avoiding barren plateaus via Gaussian Mixture Model
Xiao Shi, Yun Shang
Variational quantum algorithms is one of the most representative algorithms in quantum computing, which has a wide range of applications in quantum machine learning, quantum simula…