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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…
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…
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…
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…
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…