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Yadong Wu¹, Juan Yao², Pengfei Zhang^3,4,*, and Hui Zhai ^1,†

¹Institute for Advanced Study, Tsinghua University, Beijing, 100084, China
²Guangdong Provincial Key Laboratory of Quantum Science and Engineering, Shenzhen Institute for Quantum Science and Engineering, Southern University of Science and Technology, Shenzhen 518055, Guangdong, China
³Institute for Quantum Information and Matter, California Institute of Technology, Pasadena, California 91125, USA
⁴Walter Burke Institute for Theoretical Physics, California Institute of Technology, Pasadena, California 91125, USA

^*pengfeizhang.physics@gmail.com
^†hzhai@tsinghua.edu.cn

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Articles Citing

Expressivity of quantum neural networks

Learning to maximize quantum neural network expressivity via effective rank

A Parallel Hybrid Quantum‐Classical Convolutional Design Using Parameterized Quantum Circuits for Image Classification

Quantum image representation-based quantum neural networks for binary classification

HeteroQNN: Enabling Distributed QNN Under Heterogeneous Quantum Devices

Quantum Artificial Intelligence: From Quantum Neural Networks to Self-Programming Architectures [Feature]

Quantum circuit-based learning models: bridging quantum computing and machine learning

Quantum machine learning for complex systems: paradigms, applications, and challenges

No title available

Bee-yond the plateau: Training QNNs with swarm algorithms

Unleashing the expressive power of pulse-based quantum neural networks

Alternating and Gaussian Fermionic Isometric Tensor Network States

Predicting properties of quantum systems by regression on a quantum computer

Learning Fourier series with parametrized quantum circuits

Measuring incompatible observables with quantum neural networks

Self-supervision with quantum classifiers

Advancing quantum imaging through learning theory

Enhanced feature encoding and classification on distributed quantum hardware

Universal Approximation Theorem and Error Bounds for Quantum Neural Networks and Quantum Reservoirs

On Exploring the Potential of Quantum Auto-Encoder for Learning Quantum Systems

Hybrid Quantum ResNet for Time Series Classification

Quantum Mixture-Density Network for Multimodal Probabilistic Prediction

Hybrid quantum neural networks for efficient protein-ligand binding affinity prediction

No title available

No title available

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