Meta-learning using graph neural networks for brain connectivity regression.
-
Updated
Sep 19, 2022 - Python
Meta-learning using graph neural networks for brain connectivity regression.
A paper investigating bilateral symmetry of connectome networks.
netNorm (network normalization) framework for multi-view network integration (or fusion), recoded up in Python by Ahmed Nebli.
We provide both Matlab and Python versions of netNorm. In this folder you find the Maltab version of the code.
Research Project at DELab, UoSC, USA.
Connectome based schizophrenia prediction using structural connectivity - Deep Graph Neural Network (sc-DGNN)
Towards Deep Learning for Connectome Mapping: A Block Decomposition Framework
Rapid analysis of scientific papers from bioRxiv and PubMed
Advanced computational framework for integrated analysis of molecular and electrical brain network dynamics at the cellular level
Visualize neural networks into a heirarchial graph using networkx. Weights and signs will be respected.
Study the connectome structure in C. Elegans by finding paths between a set of neuron classes present.
Add a description, image, and links to the connectome-mapping topic page so that developers can more easily learn about it.
To associate your repository with the connectome-mapping topic, visit your repo's landing page and select "manage topics."