Quantum Adversarial Machine Learning. - Sirui Lu; Lu-Ming Duan; Dong-Ling Deng (CoRR, 2020)

Topological Quantum Compiling with Reinforcement Learning. - Yuan-Hang Zhang; Pei-Lin Zheng; Yi Zhang; Dong-Ling Deng (CoRR, 2020)

Universal Adversarial Examples and Perturbations for Quantum Classifiers. - Weiyuan Gong; Dong-Ling Deng (CoRR, 2021)

Quantum Private Distributed Learning Through Blind Quantum Computing. - Weikang Li; Sirui Lu; Dong-Ling Deng (CoRR, 2021)

Sample Complexity of Learning Quantum Circuits. - Haoyuan Cai; Qi Ye; Dong-Ling Deng (CoRR, 2021)

Quantum Continual Learning Overcoming Catastrophic Forgetting. - Wenjie Jiang; Zhide Lu; Dong-Ling Deng (CoRR, 2021)

Recent advances for quantum classifiers. - Weikang Li; Dong-Ling Deng (CoRR, 2021)

Weighted Quantum Channel Compiling through Proximal Policy Optimization. - Weiyuan Gong; Si Jiang; Dong-Ling Deng (CoRR, 2021)

Quantum Capsule Networks. - Zidu Liu; Pei-Xin Shen; Weikang Li; Lu-Ming Duan; Dong-Ling Deng (CoRR, 2022)

Quantum Neural Network Classifiers: A Tutorial. - Weikang Li; Zhide Lu; Dong-Ling Deng (CoRR, 2022)

Enhancing Quantum Adversarial Robustness by Randomized Encodings. - Weiyuan Gong; Dong Yuan 007; Weikang Li; Dong-Ling Deng (CoRR, 2022)

Experimental quantum adversarial learning with programmable superconducting qubits. - Wenhui Ren; Weikang Li; Shibo Xu; Ke Wang; Wenjie Jiang; Feitong Jin; Xuhao Zhu; Jiachen Chen; Zixuan Song; Pengfei Zhang; Hang Dong; Xu Zhang; et al. (Nat. Comput. Sci., 2022)

Expressibility-induced Concentration of Quantum Neural Tangent Kernels. - Li-Wei Yu; Weikang Li; Qi Ye; Zhide Lu; Zizhao Han; Dong-Ling Deng (CoRR, 2023)

Quantum-Classical Separations in Shallow-Circuit-Based Learning with and without Noises. - Zhihan Zhang; Weiyuan Gong; Weikang Li; Dong-Ling Deng (CoRR, 2024)

Probing many-body Bell correlation depth with superconducting qubits. - Ke Wang; Weikang Li; Shibo Xu; Mengyao Hu; Jiachen Chen; Yaozu Wu; Chuanyu Zhang; Feitong Jin; Xuhao Zhu; Yu Gao; Ziqi Tan; Aosai Zhang; et al. (CoRR, 2024)

Quantum delegated and federated learning via quantum homomorphic encryption. - Weikang Li; Dong-Ling Deng (CoRR, 2024)

Entanglement-induced provable and robust quantum learning advantages. - Haimeng Zhao; Dong-Ling Deng (CoRR, 2024)

Classical Verification of Quantum Learning Advantages with Noises. - Yinghao Ma; Jiaxi Su; Dong-Ling Deng (CoRR, 2024)

No-Free-Lunch Theories for Tensor-Network Machine Learning Models. - Jing-Chuan Wu; Qi Ye; Dong-Ling Deng; Li-Wei Yu (CoRR, 2024)

Extracting reliable quantum outputs for noisy devices. - Weikang Li; Dong-Ling Deng (Nat. Comput. Sci., 2024)

Quantum automated learning with provable and explainable trainability. - Qi Ye; Shuangyue Geng; Zizhao Han; Weikang Li; L.-M. Duan; Dong-Ling Deng (CoRR, 2025)

Solving excited states for long-range interacting trapped ions with neural networks. - Yixuan Ma; Chang Liu; Weikang Li; Shun-Yao Zhang; L.-M. Duan; Yukai Wu; Dong-Ling Deng (CoRR, 2025)