| Toward trainability of quantum neural networks K Zhang, MH Hsieh, L Liu, D Tao arXiv preprint arXiv:2011.06258, 2020 | 55 | 2020 |
| 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 | 46* | 2022 |
| 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, 2023 | 31 | 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 | 12* | 2021 |
| Toward trainability of deep quantum neural networks K Zhang, MH Hsieh, L Liu, D Tao arXiv preprint arXiv:2112.15002, 2021 | 10 | 2021 |
| Toward trainability of quantum neural networks (2020) K Zhang, MH Hsieh, L Liu, D Tao arXiv preprint arXiv:2011.06258 760, 2011 | 9 | 2011 |
| Quantum Algorithm for Finding the Negative Curvature Direction K Zhang | 3* | 2019 |
| 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 | 2 | 2023 |
| Quantum Imitation Learning Z Cheng, K Zhang, L Shen, D Tao IEEE Transactions on Neural Networks and Learning Systems, 2023 | | 2023 |
Dacheng TaoNanyang Technological UniversityVerified email at ntu.edu.sg
