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most citedThermal Neural Networks: Lumped-Parameter Thermal Modeling With State-Space Machine Learning

87 citations · 89 across the 3 of their papers we have counts for

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eess.SY2024★ 2 cited

HARDCORE: H-field and power loss estimation for arbitrary waveforms with residual, dilated convolutional neural networks in ferrite cores

Wilhelm Kirchgässner, Nikolas Förster, Till Piepenbrock +2

The MagNet Challenge 2023 calls upon competitors to develop data-driven models for the material-specific, waveform-agnostic estimation of steady-state power losses in toroidal ferr…