activity
20192026
most citedNeural Stochastic Control

4 citations · 8 across the 14 of their papers we have counts for

collaborators

15 papers

math.DS2026

Ptolemy's Equant Equates to a Universal Dynamical Clock via Machine Learning

Jingdong Zhang, Luan Yang, Murilo S. Baptista +4

Oscillatory dynamics arise ubiquitously in nonlinear systems, yet identifying a physically interpretable phase and phase dynamics in nonlinear, high-dimensional oscillations remain…

cs.LG2026

Ultra-Early Prediction of Tipping Points: Integrating Dynamical Measures with Reservoir Computing

Xin Li, Qunxi Zhu, Chengli Zhao +4

Complex dynamical systems-such as climate, ecosystems, and economics-can undergo catastrophic and potentially irreversible regime changes, often triggered by environmental paramete…

math.OC2025

Neural Event-Triggered Control with Optimal Scheduling

Luan Yang, Jingdong Zhang, Qunxi Zhu +1

Learning-enabled controllers with stability certificate functions have demonstrated impressive empirical performance in addressing control problems in recent years. Nevertheless, d…

cs.LG2024

Governing equation discovery of a complex system from snapshots

Qunxi Zhu, Bolin Zhao, Jingdong Zhang +2

Complex systems in physics, chemistry, and biology that evolve over time with inherent randomness are typically described by stochastic differential equations (SDEs). A fundamental…

math-ph2024

Learning Hamiltonian neural Koopman operator and simultaneously sustaining and discovering conservation law

Jingdong Zhang, Qunxi Zhu, Wei Lin

Accurately finding and predicting dynamics based on the observational data with noise perturbations is of paramount significance but still a major challenge presently. Here, for th…

cs.LG2024

Switched Flow Matching: Eliminating Singularities via Switching ODEs

Qunxi Zhu, Wei Lin

Continuous-time generative models, such as Flow Matching (FM), construct probability paths to transport between one distribution and another through the simulation-free learning of…