Semi-supervised time series classification
3 papers with code • 0 benchmarks • 1 datasets
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Among the many time series learning tasks of great importance, we here focus on semi-supervised learning based on a graph representation of the data.
Specifically, we propose time-series specific weak and strong augmentations and use their views to learn robust temporal relations in the proposed temporal contrasting module, besides learning discriminative representations by our proposed contextual contrasting module.