3 papers
cs.CV2026
ProMoE-FL: Prototype-conditioned Mixture of Experts for Multimodal Federated Learning with Missing Modalities
Aavash Chhetri, Bibek Niroula, Eduard Vazquez +4
In this paper, we address the problem of multimodal federated learning with missing modality. Existing methods utilize an additional public dataset or perform naive feature synthes…
cs.CV2026
Med-MMFL: A Multimodal Federated Learning Benchmark in Healthcare
Aavash Chhetri, Bibek Niroula, Pratik Shrestha +5
Federated learning (FL) enables collaborative model training across decentralized medical institutions while preserving data privacy. However, medical FL benchmarks remain scarce,…
cs.LG2025
Multimodal Federated Learning With Missing Modalities through Feature Imputation Network
Pranav Poudel, Aavash Chhetri, Prashnna Gyawali +2
Multimodal federated learning holds immense potential for collaboratively training models from multiple sources without sharing raw data, addressing both data scarcity and privacy…