127 citations · 523 across the 58 of their papers we have counts for
5 papers · 1 filter
AdaBelief Optimizer: Adapting Stepsizes by the Belief in Observed Gradients
Juntang Zhuang, Tommy Tang, Yifan Ding +4
Most popular optimizers for deep learning can be broadly categorized as adaptive methods (e.g. Adam) and accelerated schemes (e.g. stochastic gradient descent (SGD) with momentum).…
Pooling Regularized Graph Neural Network for fMRI Biomarker Analysis
Xiaoxiao Li, Yuan Zhou, Nicha C. Dvornek +4
Understanding how certain brain regions relate to a specific neurological disorder has been an important area of neuroimaging research. A promising approach to identify the salient…
Adaptive Checkpoint Adjoint Method for Gradient Estimation in Neural ODE
Juntang Zhuang, Nicha Dvornek, Xiaoxiao Li +3
Neural ordinary differential equations (NODEs) have recently attracted increasing attention; however, their empirical performance on benchmark tasks (e.g. image classification) are…
Neuropsychiatric Disease Classification Using Functional Connectomics -- Results of the Connectomics in NeuroImaging Transfer Learning Challenge
Markus D. Schirmer, Archana Venkataraman, Islem Rekik +23
Large, open-source consortium datasets have spurred the development of new and increasingly powerful machine learning approaches in brain connectomics. However, one key question re…
Multi-site fMRI Analysis Using Privacy-preserving Federated Learning and Domain Adaptation: ABIDE Results
Xiaoxiao Li, Yufeng Gu, Nicha Dvornek +3
Deep learning models have shown their advantage in many different tasks, including neuroimage analysis. However, to effectively train a high-quality deep learning model, the aggreg…