Multi-View Graph Convolutional Network and Its Applications on Neuroimage Analysis for Parkinson's Disease (AMIA 2018)
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Updated
Mar 28, 2020 - Python
Multi-View Graph Convolutional Network and Its Applications on Neuroimage Analysis for Parkinson's Disease (AMIA 2018)
Useful tools from the Network Neuroscience Lab
Integrative Analysis of Patient Health Records and Neuroimages via Memory-based Graph Convolutional Network (ICDM 2018 full paper)
Dynamical Neuroimaging Spatiotemporal Representations (DyNeuSR)
Python Machine Learning Toolbox for Brain Network Classification. Source codes are included of the top 20 teams in the Kaggle competition.
How to fuse a population of graphs into a single one using graph neural networks?
An Explainable Geometric-Weighted Graph Attention Network (xGW-GAT) for Identifying Functional Networks Associated with Gait Impairment
Implementations for CHIL 2023 paper ''PTGB: Pre-Train Graph Neural Networks for Brain Network Analysis'' and KDD 2022 paper ''Data-Efficient Brain Connectome Analysis via Multi-Task Meta-Learning''
Predicting multigraph brain population from a single graph
MGN-Net: A novel Graph Neural Network for integrating heterogenous graph population derived from multiple sources.
ABMT (Adversarial Brain Multiplex Translator) for brain graph translation using geometric generative adversarial network (gGAN).
Fast Temporal Wavelet Graph Neural Networks (NeurIPS 2023)
netNorm (network normalization) framework for multi-view network integration (or fusion), recoded up in Python by Ahmed Nebli.
Non-isomorphic Inter-modality Graph Alignment and Synthesis.
Residual Embedding Similarity-based Network Selection (RESNets) for forecasting network dynamics.
L2S-KDNet for super-resolving brain graphs using teacher-student network
Intermodalitty graph superresolution.
Neurobiologically inspired neural network models simulating, evolving, and solving tasks. Created to help understand the dynamic nature of neural networks and how our brain networks are able to adapt to changing stimuli
Classification of brain networks based on graph centrality measures
fMRI data analysis of long-covid patients
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