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eess.SP2019★ 79 cited
Classification of chaotic time series with deep learning
Nicolas Boullé, Vassilios Dallas, Yuji Nakatsukasa +1
We use standard deep neural networks to classify univariate time series generated by discrete and continuous dynamical systems based on their chaotic or non-chaotic behaviour. Our…
eess.SP2019★ 57 cited
Fast Graph Sampling Set Selection Using Gershgorin Disc Alignment
Yuanchao Bai, Fen Wang, Gene Cheung +2
Graph sampling set selection, where a subset of nodes are chosen to collect samples to reconstruct a smooth graph signal, is a fundamental problem in graph signal processing (GSP).…