4 papers
Batch Effects In Brain Foundation Model Embeddings
Ye Tao, Bradley T. Baker, Yu Wu +4
Foundation models show strong potential for large-scale, high-dimensional biomedical applications, yet their ability to capture relevant neurobiological characteristics remains und…
Rethinking Functional Brain Connectome Analysis: Do Graph Deep Learning Models Help
Keqi Han, Yao Su, Lifang He +4
Graph deep learning models, a class of AI-driven approaches employing a message aggregation mechanism, have gained popularity for analyzing the functional brain connectome in neuro…
SSFL: Discovering Sparse Unified Subnetworks at Initialization for Efficient Federated Learning
Riyasat Ohib, Bishal Thapaliya, Gintare Karolina Dziugaite +3
In this work, we propose Salient Sparse Federated Learning (SSFL), a streamlined approach for sparse federated learning with efficient communication. SSFL identifies a sparse subne…
Copula-Linked Parallel ICA: A Method for Coupling Structural and Functional MRI brain Networks
Oktay Agcaoglu, Rogers F. Silva, Deniz Alacam +3
Different brain imaging modalities offer unique insights into brain function and structure. Combining them enhances our understanding of neural mechanisms. Prior multimodal studies…