activity
20242026
most citedControlSynth Neural ODEs: Modeling Dynamical Systems with Guaranteed Convergence

3 citations · 3 across the 6 of their papers we have counts for

collaborators

8 papers

cs.RO2026

Robust Path Tracking for Vehicles via Continuous-Time Residual Learning: An ICODE-MPPI Approach

Shugen Song, Wenjie Mei, Chengyan Zhao

Model Predictive Path Integral (MPPI) control is a powerful sampling-based strategy for nonlinear autonomous systems. However, its performance is often bottlenecked by the fidelity…

math.OC2026

A Posteriori Second-Order Guarantees for Bolza Problems via Collocation

Dongzhe Zheng, Wenjie Mei

Direct collocation for Bolza optimal control yields discrete Karush-Kuhn-Tucker (KKT) points, while practical solvers expose only discrete quantities such as primal-dual iterates,…

q-bio.QM2025

Multiscale Cross-Modal Mapping of Molecular, Pathologic, and Radiologic Phenotypes in Lipid-Deficient Clear Cell Renal CellCarcinoma

Ying Cui, Dongzhe Zheng, Ke Yu +8

Clear cell renal cell carcinoma (ccRCC) exhibits extensive intratumoral heterogeneity on multiple biological scales, contributing to variable clinical outcomes and limiting the eff…

cs.RO2025

Memory-Augmented Potential Field Theory: A Framework for Adaptive Control in Non-Convex Domains

Dongzhe Zheng, Wenjie Mei

Stochastic optimal control methods often struggle in complex non-convex landscapes, frequently becoming trapped in local optima due to their inability to learn from historical traj…

cs.RO2025

Learning Dynamics under Environmental Constraints via Measurement-Induced Bundle Structures

Dongzhe Zheng, Wenjie Mei

Learning unknown dynamics under environmental (or external) constraints is fundamental to many fields (e.g., modern robotics), particularly challenging when constraint information…

cs.LG2024

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…