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Sabbaqi, M. (author), Isufi, E. (author)Devising and analysing learning models for spatiotemporal network data is of importance for tasks including forecasting, anomaly detection, and multi-agent coordination, among others. Graph Convolutional Neural Networks (GCNNs) are an established approach to learn from time-invariant network data. The graph convolution operation offers a...journal article 2023
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Lavaei, Abolfazl (author), Mohajerin Esfahani, P. (author), Zamani, Majid (author)In this work, we propose a data-driven approach for the stability analysis of discrete-time homogeneous nonlinear systems with unknown models. The proposed framework is based on constructing Lyapunov functions via a set of data, collected from trajectories of unknown systems, while providing an a-priori guaranteed confidence on the stability of...conference paper 2022