3 citations · 3 across the 9 of their papers we have counts for
4 papers · 1 filter
Learning Reduced-Order Dynamics with Singularity via Latent-Augmented Neural Ordinary Differential Equations
Xiaorui Wang, Yu Zhou, Wenjie Mei +3
This paper addresses the issue of self-intersecting trajectories (in phase space) in industrial reduced-order modeling and proposes the Latent-Augmented Neural Ordinary Differentia…
Learning and Current Prediction of PMSM Drive via Differential Neural Networks
Wenjie Mei, Xiaorui Wang, Yanrong Lu +2
Learning models for dynamical systems in continuous time is significant for understanding complex phenomena and making accurate predictions. This study presents a novel approach ut…
ControlSynth Neural ODEs: Modeling Dynamical Systems with Guaranteed Convergence
Wenjie Mei, Dongzhe Zheng, Shihua Li
Neural ODEs (NODEs) are continuous-time neural networks (NNs) that can process data without the limitation of time intervals. They have advantages in learning and understanding the…
ICODE: Modeling Dynamical Systems with Extrinsic Input Information
Zhaoyi Li, Wenjie Mei, Ke Yu +2
Learning models of dynamical systems with external inputs, which may be, for example, nonsmooth or piecewise, is crucial for studying complex phenomena and predicting future state…