4 papers
SynCo: Learning Cross-Modal Synergy by Contrasting Interaction Residuals
Yavuz Yarici, Ghassan AlRegib
Multimodal contrastive learning is a dominant paradigm for learning transferable representations from unlabeled data, but standard objectives primarily capture information that is…
MER-DG: Modality-Entropy Regularization for Multimodal Domain Generalization
Yavuz Yarici, Ghassan AlRegib
Deploying multimodal models in real-world scenarios requires generalization to new environments where recording conditions differ from training, a challenge known as multimodal dom…
RADMI: Latent Information Aggregation as a Proxy for Model Uncertainty
William Stevens, Mohit Prabhushankar, Ghassan AlRegib
Epistemic uncertainty estimation is essential for identifying regions where deep learning system outputs may be unreliable. However, existing approaches require computationally exp…
FedKPer: Tackling Generalization and Personalization in Medical Federated Learning via Knowledge Personalization
Zoe Fowler, Ghassan AlRegib
Federated learning (FL) holds great potential for medical applications. However, statistical heterogeneity across healthcare institutions poses a major challenge for FL, as the glo…