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Expressivity of quantum neural networks

Yadong Wu1, Juan Yao2, Pengfei Zhang3,4,*, and Hui Zhai1,†

  • 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

Generative invertible quantum neural networks

Armand Rousselot and Michael Spannowsky

SciPost Phys. 16 146 (2024)

Expressibility-induced concentration of quantum neural tangent kernels

Li-Wei Yu, Weikang Li, Qi Ye, Zhide Lu, Zizhao Han, and Dong-Ling Deng

Rep. Prog. Phys. 87 110501 (2024)

Quantum-inspired classification based on quantum state discrimination

Emmanuel Zambrini Cruzeiro, Christine De Mol, Serge Massar, and Stefano Pironio

Quantum Mach. Intell. 6 79 (2024)

A quantum neural network for sequential data analysis in machine learning

Phuong-Nam Nguyen

Quantum Mach. Intell. 6 88 (2024)

Quantum word embedding for machine learning

Phuong-Nam Nguyen

Phys. Scr. 99 086004 (2024)

Randomness-Enhanced Expressivity of Quantum Neural Networks

Yadong Wu, Juan Yao, Pengfei Zhang, and Xiaopeng Li

Phys. Rev. Lett. 132 010602 (2024)

Optimal depth and a novel approach to variational unitary quantum process tomography

Vladlen Galetsky, Pol Julià Farré, Soham Ghosh, Christian Deppe, and Roberto Ferrara

New J. Phys. 26 073017 (2024)

Understanding quantum machine learning also requires rethinking generalization

Elies Gil-Fuster, Jens Eisert, and Carlos Bravo-Prieto

Nat Commun 15 2277 (2024)

Benchmarking of quantum fidelity kernels for Gaussian process regression

Xuyang Guo, Jun Dai, and Roman V Krems

Mach. Learn.: Sci. Technol. 5 035081 (2024)

Quantum Hybrid Diffusion Models for Image Synthesis

Francesca De Falco, Andrea Ceschini, Alessandro Sebastianelli, Bertrand Le Saux, and Massimo Panella

Künstl Intell 38 311 (2024)

No title available

Florian Kittelmann, Pavel Sulimov, and Kurt Stockinger

Tackling Sampling Noise in Physical Systems for Machine Learning Applications: Fundamental Limits and Eigentasks

Fangjun Hu, Gerasimos Angelatos, Saeed A. Khan, Marti Vives, Esin Türeci, Leon Bello, Graham E. Rowlands, Guilhem J. Ribeill, and Hakan E. Türeci

Phys. Rev. X 13 041020 (2023)

Fermionic simulators for enhanced scalability of variational quantum simulation

Qingyu Li, Chiranjib Mukhopadhyay, and Abolfazl Bayat

Phys. Rev. Research 5 043175 (2023)

Problem-Dependent Power of Quantum Neural Networks on Multiclass Classification

Yuxuan Du, Yibo Yang, Dacheng Tao, and Min-Hsiu Hsieh

Phys. Rev. Lett. 131 140601 (2023)

Quantum Neural Network Classifiers: A Tutorial

Weikang Li, Zhi-de Lu, and Dong-Ling Deng

SciPost Phys. Lect. Notes 61 (2022)

Recent advances for quantum classifiers

Weikang Li and Dong-Ling Deng

Sci. China Phys. Mech. Astron. 65 220301 (2022)

Is Quantum Advantage the Right Goal for Quantum Machine Learning?

Maria Schuld and Nathan Killoran

PRX Quantum 3 030101 (2022)

Efficient Measure for the Expressivity of Variational Quantum Algorithms

Yuxuan Du, Zhuozhuo Tu, Xiao Yuan, and Dacheng Tao

Phys. Rev. Lett. 128 080506 (2022)

Exploring Accurate Potential Energy Surfaces via Integrating Variational Quantum Eigensolver with Machine Learning

Yanxian Tao, Xiongzhi Zeng, Yi Fan, Jie Liu, Zhenyu Li, and Jinlong Yang

J. Phys. Chem. Lett. 13 6420 (2022)

A Distributed Learning Scheme for Variational Quantum Algorithms

Yuxuan Du, Yang Qian, Xingyao Wu, and Dacheng Tao

IEEE Trans. Quantum Eng. 3 1 (2022)

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