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Data-Driven Tensor Decomposition Identification of Homogeneous Polynomial Dynamical Systems
Xin Mao, Joshua Pickard, Can Chen
Homogeneous polynomial dynamical systems (HPDSs), which can be equivalently represented by tensors, are essential for modeling higher-order networked systems, including ecological…
Maximum-Entropy Random Walks on Hypergraphs
Anqi Dong, Anzhi Sheng, Xin Mao +1
Random walks are fundamental tools for analyzing complex networked systems, including social networks, biological systems, and communication infrastructures. While classical random…
Data-driven model order reduction for T-Product-Based dynamical systems
Shenghan Mei, Ziqin He, Yidan Mei +4
Model order reduction plays a crucial role in simplifying complex systems while preserving their essential dynamic characteristics, making it an invaluable tool in a wide range of…
Data-driven Analysis of T-Product-based Dynamical Systems
Xin Mao, Anqi Dong, Ziqin He +2
A wide variety of data can be represented using third-order tensors, spanning applications in chemometrics, psychometrics, and image processing. However, traditional data-driven fr…
Controllability and Observability of Temporal Hypergraphs
Anqi Dong, Xin Mao, Can Chen
Numerous complex systems, such as those arisen in ecological networks, genomic contact networks, and social networks, exhibit higher-order and time-varying characteristics, which c…
On Complexity of Stability Analysis in Higher-order Ecological Networks through Tensor Decompositions
Anqi Dong, Can Chen
Complex ecological networks are often characterized by intricate interactions that extend beyond pairwise relationships. Understanding the stability of higher-order ecological netw…