A Graph Optimal Transport Python Package
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Updated
May 6, 2024 - Python
A Graph Optimal Transport Python Package
DYnamic Attributed Node rolEs (DYANE) is an attributed dynamic-network generative model based on temporal motifs and attributed node behavior.
✨ Implementation of Self-supervised Heterogeneous Graph Neural Network with Co-contrastive Learning with pytorch and PyG
Code for "Graph Neural Networks can Recover the Hidden Features Solely from the Graph Structure" (ICML 2023)
Unsupervised Attributed Multiplex Network Embedding (AAAI 2020)
A module to test pre-computed graph node embeddings against labeled node classification benchmarks.
Universal Graph Transformer Self-Attention Networks (TheWebConf WWW 2022) (Pytorch and Tensorflow)
Representation and learning framework for dynamic graphs using Graph Neural Networks.
Quaternion Graph Neural Networks (ACML 2021) (Pytorch and Tensorflow)
A general framework that leverages node feature information (e.g., text attributes) to efficiently generate node embeddings for previously unseen data. Instead of training individual embeddings for each node, GraphSAGE learn a function that generates embeddings by sampling and aggregating features from a node’s local neighborhood. Here, the impl…
Profiling and Deanonymizing Ethereum Users
Code and data for the CIKM2021 paper "Learning Ideological Embeddings From Information Cascades"
From Random Walks to Transformer for Learning Node Embeddings (ECML-PKDD 2020) (In Pytorch and Tensorflow)
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