19 citations · 19 across the 3 of their papers we have counts for
7 papers
Learning the dynamics of coupled oscillators from transients
Huawei Fan, Liang Wang, Yao Du +3
Whereas the importance of transient dynamics to the functionality and management of complex systems has been increasingly recognized, most of the studies are based on models. Yet i…
Learning Hamiltonian dynamics by reservoir computer
Han Zhang, Huawei Fan, Liang Wang +1
Reconstructing the KAM dynamics diagram of Hamiltonian system from the time series of a limited number of parameters is an outstanding question in nonlinear science, especially whe…
Anticipating synchronization with machine learning
Huawei Fan, Ling-Wei Kong, Ying-Cheng Lai +1
In applications of dynamical systems, situations can arise where it is desired to predict the onset of synchronization as it can lead to characteristic and significant changes in t…
Synchronization within synchronization: transients and intermittency in ecological networks
Huawei Fan, Ling-Wei Kong, Xingang Wang +2
Transients are fundamental to ecological systems with significant implications to management, conservation, and biological control. We uncover a type of transient synchronization b…
Transfer learning of chaotic systems
Yali Guo, Han Zhang, Liang Wang +2
Can a neural network trained by the time series of system A be used to predict the evolution of system B? This problem, knowing as transfer learning in a broad sense, is of great i…
Long-term prediction of chaotic systems with recurrent neural networks
Huawei Fan, Junjie Jiang, Chun Zhang +2
Reservoir computing systems, a class of recurrent neural networks, have recently been exploited for model-free, data-based prediction of the state evolution of a variety of chaotic…