4 papers
TIER-MoE: Trust-Informed Expert Routing via Conditional Modality Risk for Multimodal Fusion in Biomedical Classification
Yu Chang, Anzhe Cheng, Chenwei Wu +7
The paper proposes TIER-MoE, a risk‑guided mixture‑of‑experts framework that routes multimodal biomedical data to specialized experts based on estimated modality reliability, impro…
ERMoE: Eigen-Reparameterized Mixture-of-Experts for Stable Routing and Interpretable Specialization
Anzhe Cheng, Shukai Duan, Shixuan Li +8
Mixture-of-Experts (MoE) architectures expand model capacity by sparsely activating experts but face two core challenges: misalignment between router logits and each expert's inter…
Multi-modal Imputation for Alzheimer's Disease Classification
Abhijith Shaji, Tamoghna Chattopadhyay, Sophia I. Thomopoulos +3
Deep learning has been successful in predicting neurodegenerative disorders, such as Alzheimer's disease, from magnetic resonance imaging (MRI). Combining multiple imaging modaliti…
Diffusion Bridge Models for 3D Medical Image Translation
Shaorong Zhang, Tamoghna Chattopadhyay, Sophia I. Thomopoulos +3
Diffusion tensor imaging (DTI) provides crucial insights into the microstructure of the human brain, but it can be time-consuming to acquire compared to more readily available T1-w…