Escaping from the Barren Plateau via Gaussian Initializations in Deep Variational Quantum Circuits K Zhang, L Liu, MH Hsieh, D Tao Advances in Neural Information Processing Systems, 2022 | 85* | 2022 |
Toward trainability of quantum neural networks K Zhang, MH Hsieh, L Liu, D Tao arXiv preprint arXiv:2011.06258, 2020 | 78 | 2020 |
Recent advances for quantum neural networks in generative learning J Tian, X Sun, Y Du, S Zhao, Q Liu, K Zhang, W Yi, W Huang, C Wang, ... IEEE Transactions on Pattern Analysis and Machine Intelligence 45 (10 …, 2023 | 75 | 2023 |
Quantum Gram-Schmidt processes and their application to efficient state readout for quantum algorithms K Zhang, MH Hsieh, L Liu, D Tao Physical Review Research 3 (4), 043095, 2021 | 17* | 2021 |
Toward trainability of deep quantum neural networks K Zhang, MH Hsieh, L Liu, D Tao arXiv preprint arXiv:2112.15002, 2021 | 15 | 2021 |
Toward trainability of quantum neural networks (2020) K Zhang, MH Hsieh, L Liu, D Tao arXiv preprint arXiv:2011.06258 760, 2011 | 10 | 2011 |
Offline quantum reinforcement learning in a conservative manner Z Cheng, K Zhang, L Shen, D Tao Proceedings of the AAAI Conference on Artificial Intelligence 37 (6), 7148-7156, 2023 | 6 | 2023 |
Quantum Algorithm for Finding the Negative Curvature Direction K Zhang | 3* | 2019 |
The curse of random quantum data K Zhang, J Liu, L Liu, L Jiang, MH Hsieh, D Tao arXiv preprint arXiv:2408.09937, 2024 | 1 | 2024 |
Quantum Machine Learning: A Hands-on Tutorial for Machine Learning Practitioners and Researchers Y Du, X Wang, N Guo, Z Yu, Y Qian, K Zhang, MH Hsieh, P Rebentrost, ... arXiv preprint arXiv:2502.01146, 2025 | | 2025 |
Quantum Imitation Learning Z Cheng, K Zhang, L Shen, D Tao IEEE Transactions on Neural Networks and Learning Systems, 2023 | | 2023 |
Training Theory of Variational Quantum Machine Learning K Zhang | | 2023 |
Problem-dependent Quantum Circuit Design Based on Entropy Matching J Cheng, K Zhang, Y Xue, D Tao, Z Su | | |