Pytorch Geometric
Showing 7 of 7 projects
An autoML framework and toolkit for automating machine learning tasks on graph-structured data.
A machine learning integrations library for TypeDB, enabling graph algorithms and Graph Neural Networks on strongly-typed graph data.
A geometric deep learning model that predicts transcriptional outcomes of single and multi-gene perturbations from single-cell RNA-seq data.
GraphDTA predicts drug-target binding affinity using graph neural networks for drug discovery.
A PyTorch Geometric extension library for signed and directed graph neural networks, embedding, and clustering methods.
A PyTorch-based toolbox for graph reliability, focusing on adversarial attacks, defenses, and robustness techniques for graph neural networks.
PyTorch implementation of twin graph neural networks with similarity augmentation for drug response prediction using protein-protein associations.
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