Shypd.aiThe largest open index of AI toolsGraphCL is a Coding & Development tool that provides a PyTorch implementation for Graph Contrastive Learning with Augmentations. It focuses on pre-training Graph Neural Networks (GNNs) to address data heterogeneity in graphs.
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GraphCL offers a PyTorch implementation for Graph Contrastive Learning with Augmentations, as detailed in its NeurIPS 2020 paper. This tool is designed for pre-training Graph Neural Networks (GNNs) by leveraging contrastive learning techniques and various data augmentations. It systematically studies the performance of contrasting different augmentations across diverse datasets, including semi-supervised learning on TU Datasets, MNIST, and CIFAR10, as well as unsupervised representation learning on Cora and Citeseer. GraphCL also supports transfer learning for MoleculeNet and PPI, and adversarial robustness for component graphs. The repository provides code for these experiments and addresses potential version mismatch issues.
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