14 papers
Geometric Methods for Stochastic Dynamical Systems
Jinqiao Duan, Ting Gao, Qiao Huang +1
Geometric methods are indispensable for analyzing, predicting, and mitigating the complex behaviors inherent in nonlinear systems. In this regime, the most probable transition path…
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…
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…
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…
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…