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Laplacian Denoising Autoencoder
[article]
2020
arXiv
pre-print
While deep neural networks have been shown to perform remarkably well in many machine learning tasks, labeling a large amount of ground truth data for supervised training is usually very costly to scale. Therefore, learning robust representations with unlabeled data is critical in relieving human effort and vital for many downstream tasks. Recent advances in unsupervised and self-supervised learning approaches for visual data have benefited greatly from domain knowledge. Here we are interested
arXiv:2003.13623v1
fatcat:uel6btlupzbarey7rvr6i6ya7i