CardioState-JEPA: Delay-Aware Cross-Modal Learning of a Shared Cardiac Representation
CardioState-JEPA learns a unified cardiac representation across ECG, PPG, and PCG by predicting masked latent physiological states with cross-modal delay alignment, improving downs…
Hugging Face · Daily Papers
·Hamza Shafiq, Hung Manh Pham
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·▲ 1 upvotes
Este artigo está em destaque na seleção diária de papers do Hugging Face, curada pela comunidade de pesquisa em IA.
Autores: Hamza Shafiq, Hung Manh Pham, Bin Zhu, Pan Zhou, Jun Hu, Aaqib Saeed
- 1 upvotes da comunidade
- Temas: joint-embedding predictive architecture, cross-modal prediction, learned delay aligner, masked latent cardiac states, shared Transformer encoder, cardiac foundation model
Resumo
Resumo original (em inglês), extraído do paper:
CardioState-JEPA learns a unified cardiac representation across ECG, PPG, and PCG by predicting masked latent physiological states with cross-modal delay alignment, improving downstream classification across all three modalities.