AI Networking Cookbook: Practical recipes for AI-assisted network automation and development
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A deep learning framework combining a 1D SE-ResNet with ICU-realistic data augmentations and a physics-informed auxiliary reconstruction task based on the three-element Windkessel hemodynamic model, implemented as a differentiable forward simulation is proposed.
Bag-of-waves is presented, an interpretable framework that learns a small dictionary of recurring EEG waveform templates, called atoms, using shift-invariant k-means without labels, and works in the low-data regime where heavier models are a poor fit.
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