Nonautonomous characteristics of lump solutions for a (2+1)-dimensional Korteweg-de Vries equation with variable coefficients. - Fei-Peng Chen; Wei-Qin Chen 003; Lei Wang 097; Zhen-Jun Ye (Appl. Math. Lett., 2019)

Nonautonomous Motion Study on Accelerated and Decelerated Lump Waves for a (3 + 1)-Dimensional Generalized Shallow Water Wave Equation with Variable Coefficients. - Wei-Qin Chen 003; Qingfeng Guan 002; Chao-Fan Jiang; Fei-Fan Zhang; Lei Wang 097 (Complex., 2019)

Dynamics of transformed nonlinear waves in the (3+1)-dimensional B-type Kadomtsev-Petviashvili equation I: Transitions mechanisms. - Xue Zhang; Lei Wang 097; Wei-Qin Chen 003; Xue-Min Yao; Xin Wang; Yin-Chuan Zhao (Commun. Nonlinear Sci. Numer. Simul., 2022)

Numerical simulation for the motions of nonautonomous solitary waves of a variable-coefficient forced Burgers equation via the lattice Boltzmann method. - Qingfeng Guan 002; Wei-Qin Chen 003; Ying Li (CoRR, 2022)

Policy Gradients for Probabilistic Constrained Reinforcement Learning. - Weiqin Chen 003; Dharmashankar Subramanian; Santiago Paternain (CISS, 2023)

Open Problems and Modern Solutions for Deep Reinforcement Learning. - Weiqin Chen 003 (CoRR, 2023)

Adaptive Primal-Dual Method for Safe Reinforcement Learning. - Weiqin Chen 003; James Onyejizu; Long Vu; Lan Hoang; Dharmashankar Subramanian; Koushik Kar; Sandipan Mishra; Santiago Paternain (AAMAS, 2024)

Generalized constraint for probabilistic safe reinforcement learning. - Weiqin Chen 003; Santiago Paternain (L4DC, 2024)

A General Control-Theoretic Approach for Reinforcement Learning: Theory and Algorithms. - Weiqin Chen 003; Mark S. Squillante; Chai Wah Wu; Santiago Paternain (CoRR, 2024)

Strategist: Learning Strategic Skills by LLMs via Bi-Level Tree Search. - Jonathan Light; Min Cai; Weiqin Chen 003; Guanzhi Wang; Xiusi Chen; Wei Cheng; Yisong Yue; Ziniu Hu (CoRR, 2024)

Domain Adaptation for Offline Reinforcement Learning with Limited Samples. - Weiqin Chen 003; Sandipan Mishra; Santiago Paternain (CoRR, 2024)

SAD: State-Action Distillation for In-Context Reinforcement Learning under Random Policies. - Weiqin Chen 003; Santiago Paternain (CoRR, 2024)

PIANIST: Learning Partially Observable World Models with LLMs for Multi-Agent Decision Making. - Jonathan Light; Sixue Xing; Yuanzhe Liu 001; Weiqin Chen 003; Min Cai; Xiusi Chen; Guanzhi Wang; Wei Cheng; Yisong Yue; Ziniu Hu (CoRR, 2024)

Probabilistic Constraint for Safety-Critical Reinforcement Learning. - Weiqin Chen 003; Dharmashankar Subramanian; Santiago Paternain (IEEE Trans. Autom. Control., 2024)

Strategist: Self-improvement of LLM Decision Making via Bi-Level Tree Search. - Jonathan Light; Min Cai; Weiqin Chen 003; Guanzhi Wang; Xiusi Chen; Wei Cheng; Yisong Yue; Ziniu Hu (ICLR, 2025)

Random Policy Enables In-Context Reinforcement Learning within Trust Horizons. - Weiqin Chen 003; Santiago Paternain (Trans. Mach. Learn. Res., 2025)

Filtering Learning Histories Enhances In-Context Reinforcement Learning. - Weiqin Chen 003; Xinjie Zhang; Dharmashankar Subramanian; Santiago Paternain (CoRR, 2025)