GraphGallery is a gallery for benchmarking Graph Neural Networks, From InplusLab.
This is a PyTorch implementation of the GeniePath model in <GeniePath: Graph Neural Networks with Adaptive Receptive Paths> (https://arxiv.org/abs/1802.00910)
PoseModel: An Open-Source Toolkit for Accurate and Robust Automated Behavioral Latent Embedding
API wrapper for DolarPy
An implementation of the Graph Convolution Networks for the Cora, Citeseer, PubMed dataset.
A repo for baseline of graph pooling.
Opto-fmri decoding of locus coeruleus firing patterns using Graph Neural Networks and the BrainGNN framework
Empirical Research over the possible advantages of pretraining a Graph Neural Network for Classification by using Link Prediction. We used GCN, GAT and GraphSAGE with minibatch generation. Done for the Learning From Networks course taught by professor Fabio Vandin at the University of Padova
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