Md Asadullah Turja
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View article: Distributed Training of Large Graph Neural Networks with Variable Communication Rates
Distributed Training of Large Graph Neural Networks with Variable Communication Rates Open
Training Graph Neural Networks (GNNs) on large graphs presents unique challenges due to the large memory and computing requirements. Distributed GNN training, where the graph is partitioned across multiple machines, is a common approach to…
View article: Learning the Latent Heat Diffusion Process through Structural Brain Network from Longitudinal Amyloid-β Data
Learning the Latent Heat Diffusion Process through Structural Brain Network from Longitudinal Amyloid-β Data Open
The excessive deposition of misfolded proteins such as amyloid-β (Aβ) protein is an aging event underlying several neurodegenerative diseases. Mounting evidence shows that the spreading of neuropathological burden has a strong association …
View article: Learning Strategies for Contrast-agnostic Segmentation via SynthSeg for Infant MRI data
Learning Strategies for Contrast-agnostic Segmentation via SynthSeg for Infant MRI data Open
Longitudinal studies of infants’ brains are essential for research and clinical detection of neurodevelopmental disorders. However, for infant brain MRI scans, effective deep learning-based segmentation frameworks exist only within small a…
View article: FastSample: Accelerating Distributed Graph Neural Network Training for Billion-Scale Graphs
FastSample: Accelerating Distributed Graph Neural Network Training for Billion-Scale Graphs Open
Training Graph Neural Networks(GNNs) on a large monolithic graph presents unique challenges as the graph cannot fit within a single machine and it cannot be decomposed into smaller disconnected components. Distributed sampling-based traini…
View article: DeepGraphDMD: Interpretable Spatio-Temporal Decomposition of Non-linear Functional Brain Network Dynamics
DeepGraphDMD: Interpretable Spatio-Temporal Decomposition of Non-linear Functional Brain Network Dynamics Open
Functional brain dynamics is supported by parallel and overlapping functional network modes that are associated with specific neural circuits. Decomposing these network modes from fMRI data and finding their temporal characteristics is cha…