A publicly released conditional hierarchical VAE generates high-resolution multi-pathology ECGs and raises downstream AUROC by up to 2% over GAN baselines in transfer-learning tests.
Deep generative models for image generation: A practical comparison between varia- tional autoencoders and generative adversarial networks,
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Conditional Electrocardiogram Generation Using Hierarchical Variational Autoencoders
A publicly released conditional hierarchical VAE generates high-resolution multi-pathology ECGs and raises downstream AUROC by up to 2% over GAN baselines in transfer-learning tests.