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20242026
most citedFrom Fourier to Neural ODEs: Flow Matching for Modeling Complex Systems

1 citations · 1 across the 6 of their papers we have counts for

collaborators

7 papers

cs.LG2026

KoopCell: Koopman-Based Generative Model for Learning Single-Cell Dynamics from Distribution Snapshots

Wanfeng Lu, Yutong Zhang, Keyi Zhou +3

Learning population dynamics from temporally sparse, unpaired distribution snapshots is a fundamental challenge in developmental biology. Recent approaches based on neural differen…

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…

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…

cs.LG2024★ 1 cited

From Fourier to Neural ODEs: Flow Matching for Modeling Complex Systems

Xin Li, Jingdong Zhang, Qunxi Zhu +4

Modeling complex systems using standard neural ordinary differential equations (NODEs) often faces some essential challenges, including high computational costs and susceptibility…

math.OC2024

FESSNC: Fast Exponentially Stable and Safe Neural Controller

Jingdong Zhang, Luan Yang, Qunxi Zhu +1

In order to stabilize nonlinear systems modeled by stochastic differential equations, we design a Fast Exponentially Stable and Safe Neural Controller (FESSNC) for fast learning co…