Graph imputation neural networks augment semi-supervised datasets up to 10x by reconstructing heavily damaged samples on a similarity graph, improving over fully-supervised baselines on benchmarks.
IEEE/ACM Transactions on Audio, Speech and Language Processing 23(9), 1469–1477 (2015)
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Efficient data augmentation using graph imputation neural networks
Graph imputation neural networks augment semi-supervised datasets up to 10x by reconstructing heavily damaged samples on a similarity graph, improving over fully-supervised baselines on benchmarks.