CLOCS: contrastive learning of cardiac signals across space, time, and patients
The healthcare industry generates troves of unlabelled physiological data. This data can be exploited via contrastive learning, a self-supervised pre-training method that encourages representations of instances to be similar to one another. We propose a family of contrastive learning methods, CLOCS,...
| Main Authors: | , , |
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| Format: | Journal article |
| Language: | English |
| Published: |
Journal of Machine Learning Research
2021
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