netFound is a pretrained network foundation model using protocol-aware tokenization, context embedding, hierarchical attention, and privacy design that reaches F1 0.95 on exogenous context discrimination versus under 0.62 for prior models.
Auto-encoding variational bayes,
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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.
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netFound: Principled Design for Network Foundation Models
netFound is a pretrained network foundation model using protocol-aware tokenization, context embedding, hierarchical attention, and privacy design that reaches F1 0.95 on exogenous context discrimination versus under 0.62 for prior models.
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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.