Learning Dynamic Systems Using Gaussian Process Regression with Analytic Ordinary Differential Equations as Prior Information. - Shengbing Tang; Kenji Fujimoto; Ichiro Maruta (IEICE Trans. Inf. Syst., 2021)

Learning dynamical systems using a novel multiple-output Gaussian process model. - Shengbing Tang; Kenji Fujimoto; Ichiro Maruta (ICMLT, 2022)

Actively Learning Gaussian Process Dynamical Systems Through Global and Local Explorations. - Shengbing Tang; Kenji Fujimoto; Ichiro Maruta (IEEE Access, 2022)

Actively learning dynamical systems using Bayesian neural networks. - Shengbing Tang; Kenji Fujimoto; Ichiro Maruta (Appl. Intell., 2023)

Hologram Reasoning for Solving Algebra Problems with Geometry Diagrams. - Litian Huang; Xinguo Yu; Feng Xiong; Bin He; Shengbing Tang; Jiawen Fu (CoRR, 2024)

Physics-informed multi-output Gaussian process for dynamical system modeling. - Shengbing Tang; Bin He 007; Xinguo Yu (Neural Networks, 2025)

Bayesian math word problem solvers with credibility level: know what they know and what they do not know. - Shengbing Tang; Bin He; Xinguo Yu (Neural Comput. Appl., 2025)