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Appraisal of data-driven and mechanistic emulators of nonlinear hydrodynamic urban drainage simulators
In this paper, we therefore compare the performance of two families of emulators for open channel flows in the context of urban drainage simulators.
Memristor models for machine learning
In this work, we explore the use of memristor networks for analog approximate computation, based on a machine learning framework called reservoir computing.
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