“unsupervised learning”

Equivariance-based self-supervised learning for audio signal recovery from clipped measurements

Abstract: In numerous inverse problems, state-of-the-art solving strategies involve training neural networks from ground truth and associated measurement datasets that, however, may be expensive or impossible to collect. Recently, self-supervised learning techniques have emerged, with the major advantage of no longer requiring ground truth data.