| Diversity-sensitive conditional generative adversarial networks D Yang, S Hong, Y Jang, T Zhao, H Lee arXiv preprint arXiv:1901.09024, 2019 | 222 | 2019 |
| Learning self-consistency for deepfake detection T Zhao, X Xu, M Xu, H Ding, Y Xiong, W Xia Proceedings of the IEEE/CVF international conference on computer vision …, 2021 | 220 | 2021 |
| Adversarial defense via learning to generate diverse attacks Y Jang, T Zhao, S Hong, H Lee Proceedings of the IEEE/CVF International Conference on Computer Vision …, 2019 | 84 | 2019 |
| Natural evolution strategies and variational Monte Carlo T Zhao, G Carleo, J Stokes, S Veerapaneni Machine Learning: Science and Technology 2 (2), 02LT01, 2020 | 22 | 2020 |
| Overcoming barriers to scalability in variational quantum Monte Carlo T Zhao, S De, B Chen, J Stokes, S Veerapaneni Proceedings of the International Conference for High Performance Computing …, 2021 | 17 | 2021 |
| Scalable neural quantum states architecture for quantum chemistry T Zhao, J Stokes, S Veerapaneni Machine Learning: Science and Technology 4 (2), 025034, 2023 | 16 | 2023 |
| Natural evolution strategies and quantum approximate optimization T Zhao, G Carleo, J Stokes, S Veerapaneni Preprint at https://arxiv. org/pdf/2005.04447. pdf, 2020 | 6 | 2020 |
| Quantum-inspired variational algorithms for partial differential equations: application to financial derivative pricing T Zhao, C Sun, A Cohen, J Stokes, S Veerapaneni Quantitative Finance 24 (1), 1-11, 2023 | 4 | 2023 |
| Meta variational monte carlo T Zhao, J Stokes, O Knitter, B Chen, S Veerapaneni arXiv preprint arXiv:2011.10614, 2020 | 4 | 2020 |
| Meta-variational quantum Monte Carlo T Zhao, J Stokes, S Veerapaneni Quantum Machine Intelligence 5 (1), 5, 2023 | | 2023 |
| Neural Quantum States for Scientific Computing: Applications to Computational Chemistry and Finance T Zhao | | 2022 |
