Weiqin Chen

According to our database, Weiqin Chen authored at least 19 papers between 2019 and 2026.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of three.

2026

Provable Domain Adaptation for Offline Reinforcement Learning with Limited Samples.

Weiqin Chen, Xinjie Zhang, Sandipan Mishra, Santiago Paternain

Trans. Mach. Learn. Res., 2026

2025

ConstrainedSQL: Training LLMs for Text2SQL via Constrained Reinforcement Learning.

Weiqin Chen, Nhan Huu Pham, Michael Robert Glass, Long Hai Vu, Gaetano Rossiello, Dharmashankar Subramanian, Santiago Paternain

CoRR, November, 2025

Filtering Learning Histories Enhances In-Context Reinforcement Learning.

Weiqin Chen, Xinjie Zhang, Dharmashankar Subramanian, Santiago Paternain

CoRR, May, 2025

Random Policy Enables In-Context Reinforcement Learning within Trust Horizons.

Weiqin Chen, Santiago Paternain

Trans. Mach. Learn. Res., 2025

Strategist: Self-improvement of LLM Decision Making via Bi-Level Tree Search.

Jonathan Light, Min Cai, Weiqin Chen, Guanzhi Wang, Xiusi Chen, Wei Cheng, Yisong Yue, Ziniu Hu

Proceedings of the Thirteenth International Conference on Learning Representations, 2025

2024

Probabilistic Constraint for Safety-Critical Reinforcement Learning.

Weiqin Chen, Dharmashankar Subramanian, Santiago Paternain

IEEE Trans. Autom. Control., October, 2024

PIANIST: Learning Partially Observable World Models with LLMs for Multi-Agent Decision Making.

Jonathan Light, Sixue Xing, Yuanzhe Liu, Weiqin Chen, Min Cai, Xiusi Chen, Guanzhi Wang, Wei Cheng, Yisong Yue, Ziniu Hu

CoRR, 2024

SAD: State-Action Distillation for In-Context Reinforcement Learning under Random Policies.

Weiqin Chen, Santiago Paternain

CoRR, 2024

Domain Adaptation for Offline Reinforcement Learning with Limited Samples.

Weiqin Chen, Sandipan Mishra, Santiago Paternain

CoRR, 2024

Strategist: Learning Strategic Skills by LLMs via Bi-Level Tree Search.

Jonathan Light, Min Cai, Weiqin Chen, Guanzhi Wang, Xiusi Chen, Wei Cheng, Yisong Yue, Ziniu Hu

CoRR, 2024

A General Control-Theoretic Approach for Reinforcement Learning: Theory and Algorithms.

Weiqin Chen, Mark S. Squillante, Chai Wah Wu, Santiago Paternain

CoRR, 2024

Generalized constraint for probabilistic safe reinforcement learning.

Weiqin Chen, Santiago Paternain

Proceedings of the 6th Annual Learning for Dynamics & Control Conference, 2024

Adaptive Primal-Dual Method for Safe Reinforcement Learning.

Weiqin Chen, James Onyejizu, Long Vu, Lan Hoang, Dharmashankar Subramanian, Koushik Kar, Sandipan Mishra, Santiago Paternain

Proceedings of the 23rd International Conference on Autonomous Agents and Multiagent Systems, 2024

2023

Open Problems and Modern Solutions for Deep Reinforcement Learning.

Weiqin Chen

CoRR, 2023

Policy Gradients for Probabilistic Constrained Reinforcement Learning.

Weiqin Chen, Dharmashankar Subramanian, Santiago Paternain

Proceedings of the 57th Annual Conference on Information Sciences and Systems, 2023

2022

Numerical simulation for the motions of nonautonomous solitary waves of a variable-coefficient forced Burgers equation via the lattice Boltzmann method.

Qingfeng Guan, Wei-Qin Chen, Ying Li

CoRR, 2022

Dynamics of transformed nonlinear waves in the (3+1)-dimensional B-type Kadomtsev-Petviashvili equation I: Transitions mechanisms.

Xue Zhang, Lei Wang, Wei-Qin Chen, Xue-Min Yao, Xin Wang, Yin-Chuan Zhao

Commun. Nonlinear Sci. Numer. Simul., 2022

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, Qingfeng Guan, Chao-Fan Jiang, Fei-Fan Zhang, Lei Wang

Complex., 2019

Nonautonomous characteristics of lump solutions for a (2+1)-dimensional Korteweg-de Vries equation with variable coefficients.

Fei-Peng Chen, Wei-Qin Chen, Lei Wang, Zhen-Jun Ye

Appl. Math. Lett., 2019