4 citations · 12 across the 18 of their papers we have counts for
21 papers
Nonlocal Hamiltonian Dynamics on Sparse Lévy Graphs: Spectral Analysis and Multimodal Sampling
Miaolei Zheng, Ting Gao, Jinqiao Duan
We develop a sparse graph method for transporting probability mass toward multimodal target distributions through damped nonlocal Hamiltonian dynamics. The formulation combines log…
Geometric Methods for Stochastic Dynamical Systems: A Concise Introduction
Jinqiao Duan, Ting Gao, Qiao Huang +1
There is growing interest in stochastic dynamics in the applied mathematics, interdis-ciplinary science, and artificial intelligence communities. This book is written primarilyfor…
Joint Discovery of Graph Structure and Dynamics in Stochastic Interacting Particle Systems
Demao Liu, Ting Gao, Jinqiao Duan
We study the joint identification of network structure and governing dynamics in stochastic interacting particle systems, which consist of an unknown directed weighted interaction…
Efficient Encrypted Computation in Convolutional Spiking Neural Networks with TFHE
Longfei Guo, Pengbo Li, Ting Gao +3
With the rapid advancement of AI technology, we have seen more and more concerns on data privacy, leading to some cutting-edge research on machine learning with encrypted computati…
A Jacobi Field Approach to Splitting Detection in Schrödinger Bridge
Chunhai Jiao, Jin Guo, Haoyan Zhang +2
We study the problem of detecting the onset of path splitting in stochastic interpolation between probability distributions. This question is especially subtle when the target dist…
Beyond Distance: Quantifying Point Cloud Dynamics with Persistent Homology and Dynamic Optimal Transport
Yixin Wang, Ting Gao, Jinqiao Duan
We introduce a framework for analyzing topological tipping in time-evolutionary point clouds by extending the recently proposed Topological Optimal Transport (TpOT) distance. While…
Predicting the onset of period-doubling bifurcations via dominant eigenvalue extracted from autocorrelation
Zhiqin Ma, Chunhua Zeng, Ting Gao +1
Predicting the occurrence of transitions in the qualitative dynamics of many natural systems is crucial, yet it remains a challenging task. Generic early warning signals like varia…
Learning Lévy density via adaptive RKHS regression with bi-level optimization
Luxuan Yang, Fei Lu, Ting Gao +2
We propose a nonparametric method to learn the Lévy density from probability density data governed by a nonlocal Fokker-Planck equation. We recast the problem as identifying the ke…
Artificial intelligence as a surrogate brain: Bridging neural dynamical models and data
Yinuo Zhang, Demao Liu, Zhichao Liang +6
Recent breakthroughs in artificial intelligence (AI) are reshaping the way we construct computational counterparts of the brain, giving rise to a new class of ``surrogate brains''.…
Adaptive control for multi-scale stochastic dynamical systems with stochastic next generation reservoir computing
Jiani Cheng, Ting Gao, Jinqiao Duan
The rapid advancement of neuroscience and machine learning has established data-driven stochastic dynamical system modeling as a powerful tool for understanding and controlling hig…
Critical Transitions in Interacting Particle Systems: An Onsager-Machlup Action Functional Framework
Jianyu Chen, Ting Gao, Galina Strelkova +1
This paper establishes an indirect approximation theorem for the most probable transition pathway of a stochastic interacting particle system in the mean-field framework. This pape…
Action Functional as an Early Warning Indicator in the Space of Probability Measures via Schrödinger Bridge
Peng Zhang, Ting Gao, Jin Guo +1
Critical transitions and tipping phenomena between two meta-stable states in stochastic dynamical systems are a significant scientific issue. In this work, we expand the methodolog…
Fourier neural operator based fluid-structure interaction for predicting the vesicle dynamics
Wang Xiao, Ting Gao, Kai Liu +2
Solving complex fluid-structure interaction (FSI) problems, characterized by nonlinear partial differential equations, is crucial in various scientific and engineering applications…
Early Warning Prediction with Automatic Labeling in Epilepsy Patients
Peng Zhang, Ting Gao, Jin Guo +2
Early warning for epilepsy patients is crucial for their safety and well-being, in particular to prevent or minimize the severity of seizures. Through the patients' EEG data, we pr…
Privacy-Preserving Discretized Spiking Neural Networks
Pengbo Li, Ting Gao, Huifang Huang +4
The rapid development of artificial intelligence has brought considerable convenience, yet also introduces significant security risks. One of the research hotspots is to balance da…
Learning Stochastic Dynamical Systems as an Implicit Regularization with Graph Neural Networks
Jin Guo, Ting Gao, Yufu Lan +3
Stochastic Gumbel graph networks are proposed to learn high-dimensional time series, where the observed dimensions are often spatially correlated. To that end, the observed randomn…
Reservoir Computing with Error Correction: Long-term Behaviors of Stochastic Dynamical Systems
Cheng Fang, Yubin Lu, Ting Gao +1
The prediction of stochastic dynamical systems and the capture of dynamical behaviors are profound problems. In this article, we propose a data-driven framework combining Reservoir…
Deep Reinforcement Learning in Finite-Horizon to Explore the Most Probable Transition Pathway
Jin Guo, Ting Gao, Peng Zhang +2
In many scientific and engineering problems, noise and nonlinearity are unavoidable, which could induce interesting mathematical problem such as transition phenomena. This paper fo…
Multi-task Meta Label Correction for Time Series Prediction
Luxuan Yang, Ting Gao, Wei Wei +3
Time series classification faces two unavoidable problems. One is partial feature information and the other is poor label quality, which may affect model performance. To address th…
Fokker-Planck Equations for Stochastic Dynamical Systems with Symmetric Lévy Motions
Ting Gao, Jinqiao Duan, Xiaofan Li
The Fokker-Planck equations for stochastic dynamical systems, with non-Gaussian stable symmetric Lévy motions, have a nonlocal or fractional Laplacian term. This nonlocality is…
Mean exit time and escape probability for dynamical systems driven by Levy noise
Ting Gao, Jinqiao Duan, Xiaofan Li +1
The mean first exit time and escape probability are utilized to quantify dynamical behaviors of stochastic differential equations with non-Gaussian alpha-stable type Levy motions.…