2 papers
cs.LG2025
Foundational Models and Federated Learning: Survey, Taxonomy, Challenges and Practical Insights
Cosmin-Andrei Hatfaludi, Alex Serban
Federated learning has the potential to unlock siloed data and distributed resources by enabling collaborative model training without sharing private data. As more complex foundati…
cs.CV2025
ConceptVAE: Self-Supervised Fine-Grained Concept Disentanglement from 2D Echocardiographies
Costin F. Ciusdel, Alex Serban, Tiziano Passerini
While traditional self-supervised learning methods improve performance and robustness across various medical tasks, they rely on single-vector embeddings that may not capture fine-…