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TopTimeNet: Topologically-assisted time-series classification model

Sayyad, Sharareh et al.
arXiv (All) · Papers
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applied-physicschaotic-dynamicscomputational-geometrydynamical-systemsmachine-learning
Distinguishing periodic from chaotic dynamics in a time series is a fundamental challenge in both physics and engineering. Yet, end-to-end learned architectures must discover both a representation and a decision boundary from data, at substantial cost. We introduce TopTimeNet, which decouples these
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