NAGFS (Network Atlas-Guided Feature Selection) for a fast and accurate graph data classification code, recoded by Dogu Can ELCI.
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Updated
Mar 30, 2020 - Python
NAGFS (Network Atlas-Guided Feature Selection) for a fast and accurate graph data classification code, recoded by Dogu Can ELCI.
Python Machine Learning Toolbox for Brain Network Classification. Source codes are included of the top 20 teams in the Kaggle competition.
netNorm (network normalization) framework for multi-view network integration (or fusion), recoded up in Python by Ahmed Nebli.
Brain Graph Super-Resolution: how to generate high-resolution graphs from low-resolution graphs? (Python3 version)
ABMT (Adversarial Brain Multiplex Translator) for brain graph translation using geometric generative adversarial network (gGAN).
HCAE (HyperConnectome AutoEncoder) for brain state identification.
Topology-guided cyclic graph generation using GCNs.
Learning-guided Graph Dual Adversarial Domain Alignment (LG-DADA) framework for predicting a target graph from a source graph.
Graph SuperResolution Network using geometric deep learning.
Predicting the multi-trajectory evolution of multimodal brain connectivity.
L2S-KDNet for super-resolving brain graphs using teacher-student network
One-representative shot learning for graph classification.
Recurrent Dynamic Graph Mapper using GNN
Non-isomorphic Inter-modality Graph Alignment and Synthesis.
Federated multigraph integration with application to connectional brain template estimation.
Intermodalitty graph superresolution.
Recurrent multigraph integrator network using graph neural network.
Multigraph fusion and classification network using graph neural network
MGN-Net: A novel Graph Neural Network for integrating heterogenous graph population derived from multiple sources.
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