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Found 3 papers, 1 papers with code
Towards Sleep Scoring Generalization Through Self-Supervised Meta-Learning
In this work we introduce a novel meta-learning method for sleep scoring based on self-supervised learning.
Generative Adversarial Learning via Kernel Density Discrimination
We show a boost in the quality of generated samples with respect to FID from 10% to 40% compared to the baseline.
Boosting Generalization in Bio-Signal Classification by Learning the Phase-Amplitude Coupling
Various hand-crafted features representations of bio-signals rely primarily on the amplitude or power of the signal in specific frequency bands.
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