3 papers
eess.IV2026
FlexiBrain: Resolution-Agnostic Voxel-Level Encoding for Native fMRI
Mo Wang, Wenhao Ye, Junfeng Xia +3
The success of large-scale deep learning models in neuroscience is fundamentally constrained by severe data heterogeneity. Native fMRI data aggregated from diverse sources exhibit…
cs.CE2026
Omni-fMRI: A Universal Atlas-Free fMRI Foundation Model
Mo Wang, Wenhao Ye, Junfeng Xia +6
Self-supervised fMRI foundation models have shown promising transfer performance, yet most rely on predefined region-level parcellations that discard fine-grained voxel information…
cs.LG2024
No More Adam: Learning Rate Scaling at Initialization is All You Need
Minghao Xu, Lichuan Xiang, Xu Cai +1
In this work, we question the necessity of adaptive gradient methods for training deep neural networks. SGD-SaI is a simple yet effective enhancement to stochastic gradient descent…