activity
20202023
most citedA Data-Driven Approach for Discovering Stochastic Dynamical Systems with Non-Gaussian Levy Noise

77 citations · 214 across the 11 of their papers we have counts for

collaborators

11 papers

stat.ML2023

Computing large deviation prefactors of stochastic dynamical systems based on machine learning

Yang Li, Shenglan Yuan, Linghongzhi Lu +1

In this paper, we present large deviation theory that characterizes the exponential estimate for rare events of stochastic dynamical systems in the limit of weak noise. We aim to c…

math.OC2023

Detecting the Most Probable High Dimensional Transition Pathway Based on Optimal Control Theory

Jianyu Chen, Ting Gao, Yang Li +1

Many natural systems exhibit phase transition where external environmental conditions spark a shift to a new and sometimes quite different state. Therefore, detecting the behavior…

stat.ML2022★ 7 cited

Controlling mean exit time of stochastic dynamical systems based on quasipotential and machine learning

Yang Li, Shenglan Yuan, Shengyuan Xu

The mean exit time escaping basin of attraction in the presence of white noise is of practical importance in various scientific fields. In this work, we propose a strategy to contr…

stat.ML2021

Extracting stochastic dynamical systems with -stable Lévy noise from data

Yang Li, Yubin Lu, Shengyuan Xu +1

With the rapid increase of valuable observational, experimental and simulated data for complex systems, much efforts have been devoted to identifying governing laws underlying the…

math.DS2021★ 17 cited

Extracting Stochastic Governing Laws by Nonlocal Kramers-Moyal Formulas

Yubin Lu, Yang Li, Jinqiao Duan

With the rapid development of computational techniques and scientific tools, great progress of data-driven analysis has been made to extract governing laws of dynamical systems fro…

math.ST2021★ 27 cited

Extracting Governing Laws from Sample Path Data of Non-Gaussian Stochastic Dynamical Systems

Yang Li, Jinqiao Duan

Advances in data science are leading to new progresses in the analysis and understanding of complex dynamics for systems with experimental and observational data. With numerous phy…