87 citations · 221 across the 37 of their papers we have counts for
41 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…
History-Conditioned Inference of Memory and Stochastic Forcing in Generalized Langevin Equations under Lévy Noise
Yang Yang, Ting Gao, Xiaoli Chen
We consider the identification of memory and stochastic forcing in a one-dimensional generalized Langevin equation with state-dependent Brownian noise and optional additive symmetr…
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…
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…
Early warning prediction: Onsager-Machlup vs Schrödinger
Xiaoai Xu, Yixuan Zhou, Xiang Zhou +2
Predicting critical transitions in complex systems, such as epileptic seizures in the brain, represents a major challenge in scientific research. The high-dimensional characteristi…
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''.…
Latent Iterative Refinement Flow: A Geometric Constrained Approach for Few-Shot Generation
Songtao Li, Tianqi Hou, Zhenyu Liao +1
Diffusion and flow-matching models trained with limited data often tend to memorize the training data instead of generalization, leading to severely reduced diversity. In this pape…
NeuronSeek: On Stability and Expressivity of Task-driven Neurons
Hanyu Pei, Jing-Xiao Liao, Qibin Zhao +4
Drawing inspiration from our human brain that designs different neurons for different tasks, recent advances in deep learning have explored modifying a network's neurons to develop…
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…
Hedging with Sparse Reward Reinforcement Learning
Yiheng Ding, Gangnan Yuan, Dewei Zuo +1
Derivatives, as a critical class of financial instruments, isolate and trade the price attributes of risk assets such as stocks, commodities, and indices, aiding risk management an…
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…
Efficient Privacy-Preserving Convolutional Spiking Neural Networks with FHE
Pengbo Li, Huifang Huang, Ting Gao +2
With the rapid development of AI technology, we have witnessed numerous innovations and conveniences. However, along with these advancements come privacy threats and risks. Fully H…
Well-posedness and averaging principle for Lévy-type McKean-Vlasov stochastic differential equations under local Lipschitz conditions
Ying Chao, Jinqiao Duan, Ting Gao +1
In this paper, we investigate a class of McKean-Vlasov stochastic differential equations under Lévy-type perturbations. We first establish the existence and uniqueness theorem for…
Early warning indicators via latent stochastic dynamical systems
Lingyu Feng, Ting Gao, Wang Xiao +1
Detecting early warning indicators for abrupt dynamical transitions in complex systems or high-dimensional observation data is essential in many real-world applications, such as br…
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…