Zhang, Yiming

Strong Quantum Computational Advantage Using a Superconducting Quantum Processor

Wu, Y., Bao, W.-S., Cao, S., Chen, F., Chen, M.-C., Chen, X., Chung, T.-H., Deng, H., Du, Y., Fan, D., et al. (2021) · Physical Review Letters

Quantum Computing Algorithms and ArchitectureQuantum Information and Cryptography

Cited by 1,059

Realization of an Error-Correcting Surface Code with Superconducting Qubits

Zhao, Y., Ye, Y., Huang, H.-L., Zhang, Y., Wu, D., Guan, H., Zhu, Q., Wei, Z., He, T., Cao, S., et al. (2022) · Physical Review Letters

Quantum Computing Algorithms and ArchitectureQuantum Information and Cryptography

Cited by 321

Quantum computational advantage via 60-qubit 24-cycle random circuit sampling

Zhu, Q., Cao, S., Chen, F., Chen, M.-C., Chen, X., Chung, T.-H., Deng, H., Du, Y., Fan, D., Gong, M., et al. (2022) · Science Bulletin

Quantum Computing Algorithms and ArchitectureQuantum Information and Cryptography

Cited by 263

DNN Filter Bank Cepstral Coefficients for Spoofing Detection

Yu, H., Tan, Z.-H., Zhang, Y., Ma, Z., & Guo, J. (2017) · IEEE Access

Speech Recognition and SynthesisSpeech and Audio Processing

Cited by 67

Diagonalwise Refactorization: An Efficient Training Method for Depthwise Convolutions

Qin, Z., Zhang, Z., Li, D., Zhang, Y., & Peng, Y. (2018) · 2018 International Joint Conference on Neural Networks (IJCNN)

Advanced Neural Network ApplicationsParallel Computing and Optimization Techniques

Cited by 27