Achieving Mean-Variance Efficiency by Continuous-Time Reinforcement Learning. - Yilie Huang; Yanwei Jia; Xun Yu Zhou (ICAIF, 2022)

Policy Evaluation and Temporal-Difference Learning in Continuous Time and Space: A Martingale Approach. - Yanwei Jia; Xun Yu Zhou (J. Mach. Learn. Res., 2022)

Policy Gradient and Actor-Critic Learning in Continuous Time and Space: Theory and Algorithms. - Yanwei Jia; Xun Yu Zhou (J. Mach. Learn. Res., 2022)

Learning Merton's Strategies in an Incomplete Market: Recursive Entropy Regularization and Biased Gaussian Exploration. - Min Dai; Yuchao Dong; Yanwei Jia; Xun Yu Zhou (CoRR, 2023)

q-Learning in Continuous Time. - Yanwei Jia; Xun Yu Zhou (J. Mach. Learn. Res., 2023)

Herding in Probabilistic Forecasts. - Yanwei Jia; Jussi Keppo; Ville A. Satopää (Manag. Sci., 2023)

Continuous-time Risk-sensitive Reinforcement Learning via Quadratic Variation Penalty. - Yanwei Jia (CoRR, 2024)

Sublinear Regret for An Actor-Critic Algorithm in Continuous-Time Linear-Quadratic Reinforcement Learning. - Yilie Huang; Yanwei Jia; Xun Yu Zhou (CoRR, 2024)

Mean-Variance Portfolio Selection by Continuous-Time Reinforcement Learning: Algorithms, Regret Analysis, and Empirical Study. - Yilie Huang; Yanwei Jia; Xun Yu Zhou (CoRR, 2024)

Accuracy of Discretely Sampled Stochastic Policies in Continuous-time Reinforcement Learning. - Yanwei Jia; Du Ouyang; Yufei Zhang (CoRR, 2025)