Publications
2026
| [11] | Schrödinger bridge with transport relaxation. Preprint. (arXiv) With Renyuan Xu and Luhao Zhang |
2025
| [10] | Wasserstein distributional adversarial training for deep neural networks. Preprint. (arXiv) With Xingjian Bai, Guangyi He, and Jan Obłój |
| [9] | A transfer principle for computing the adapted Wasserstein distance between stochastic processes. Preprint. (arXiv) With Fang Rui Lim |
2024
| [8] | Duality of causal distributionally robust optimization: the discrete-time case. To appear in SIAM Journal on Control and Optimization. (arXiv) |
| [7] | The anytime convergence of stochastic gradient descent with momentum: from a continuous-time perspective. Preprint. (arXiv) With Yasong Feng, Tianyu Wang, and Zhiliang Ying |
| [6] | Sensitivity of causal distributionally robust optimization. Preprint. (arXiv) With Jan Obłój |
2023
| [5] | Sequential propagation of chaos. To appear in Acta Mathematica Sinica. (arXiv) With Kai Du and Xiaochen Li |
| [4] | Empirical approximation to invariant measures for McKean–Vlasov processes: mean-field interaction vs self-interaction. Bernoulli, vol. 29, no. 3, pp. 2492–2518. (DOI) (arXiv) With Kai Du and Jinfeng Li |
| [3] | Wasserstein distributional robustness of neural networks. Advances in Neural Information Processing Systems, pp. 26322–26347. (DOI) (arXiv) With Xingjian Bai, Guangyi He, and Jan Obłój |
2022
| [2] | Existence and distributional chaos of points that are recurrent but not Banach recurrent. Journal of Dynamics and Differential Equations. (DOI) (arXiv) With Xueting Tian |
2021
| [1] | Convergence of the Deep BSDE method for FBSDEs with non-Lipschitz coefficients. Probability, Uncertainty and Quantitative Risk, vol. 6, no. 4, pp. 391–408. (DOI) (arXiv) With Jinfeng Li |