5 papers
Sparse Kalman Identification for Partially Observable Systems via Adaptive Bayesian Learning
Jilan Mei, Tengjie Zheng, Lin Cheng +2
Sparse dynamics identification is an essential tool for discovering interpretable physical models and enabling efficient control in engineering systems. However, existing methods r…
Recursive Inference for Heterogeneous Multi-Output GP State-Space Models with Arbitrary Moment Matching
Tengjie Zheng, Jilan Mei, Di Wu +2
Accurate learning of system dynamics is becoming increasingly crucial for advanced control and decision-making in engineering. However, real-world systems often exhibit multiple ch…
Confidence-Aware Learning Optimal Terminal Guidance via Gaussian Process Regression
Han Wang, Donghe Chen, Tengjie Zheng +2
Modern aerospace guidance systems demand rigorous constraint satisfaction, optimal performance, and computational efficiency. Traditional analytical methods struggle to simultaneou…
Error Distribution Smoothing:Advancing Low-Dimensional Imbalanced Regression
Donghe Chen, Jiaxuan Yue, Tengjie Zheng +2
In real-world regression tasks, datasets frequently exhibit imbalanced distributions, characterized by a scarcity of data in high-complexity regions and an abundance in low-complex…
Adviser-Actor-Critic: Eliminating Steady-State Error in Reinforcement Learning Control
Donghe Chen, Yubin Peng, Tengjie Zheng +3
High-precision control tasks present substantial challenges for reinforcement learning (RL) algorithms, frequently resulting in suboptimal performance attributed to network approxi…