Universal Graph Transformer Self-Attention Networks (TheWebConf WWW 2022) (Pytorch and Tensorflow)

Unsupervised Attributed Multiplex Network Embedding (AAAI 2020)

Profiling and Deanonymizing Ethereum Users

Quaternion Graph Neural Networks (ACML 2021) (Pytorch and Tensorflow)

From Random Walks to Transformer for Learning Node Embeddings (ECML-PKDD 2020) (In Pytorch and Tensorflow)

Code for "Graph Neural Networks can Recover the Hidden Features Solely from the Graph Structure" (ICML 2023)

Representation and learning framework for dynamic graphs using Graph Neural Networks.

Code and data for the CIKM2021 paper "Learning Ideological Embeddings From Information Cascades"

DEBS 2021: Graph Stream Analytics tutorial

✨ Implementation of Self-supervised Heterogeneous Graph Neural Network with Co-contrastive Learning with pytorch and PyG

Data and code repository from "Time-varying graph representation learning via higher-order skip-gram with negative sampling"

CS224W: Graph Embedding, GNNs, Recommendation Systems, and applications.

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…

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.

📌Graph Convolutional Network (GCN) on Zachary's karate club network

Various Network Science Projects (2021-2022)

Source Code for the AAAI 2020 oral paper - Dynamic Embedding on Textual Networks via a Gaussian Process.

A module to test pre-computed graph node embeddings against labeled node classification benchmarks.