Universal Graph Transformer Self-Attention Networks (TheWebConf WWW 2022) (Pytorch and Tensorflow)
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Updated
Aug 16, 2022 - Python
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 and data for the CIKM2021 paper "Learning Ideological Embeddings From Information Cascades"
CS224W: Graph Embedding, GNNs, Recommendation Systems, and applications.
Code for "Graph Neural Networks can Recover the Hidden Features Solely from the Graph Structure" (ICML 2023)
(EPJ DS) Time-varying graph representation learning via higher-order skip-gram with negative sampling
A team project for the course Algorithm Analysis and Design at IIIT-Hyderabad. Primarily features modelling the stock market as a graph, testing the metrics of numerous algorithms for modeling correlation networks and detecting market fragmentation.
DYnamic Attributed Node rolEs (DYANE) is an attributed dynamic-network generative model based on temporal motifs and attributed node behavior.
Source Code for the AAAI 2020 oral paper - Dynamic Embedding on Textual Networks via a Gaussian Process.
✨ Implementation of Self-supervised Heterogeneous Graph Neural Network with Co-contrastive Learning with pytorch and PyG
Representation and learning framework for dynamic graphs using Graph Neural Networks.
Source code for the paper "Zhicheng He, Jie Liu*, Na Li, and Yalou Huang. Learning Network-to-Network Model for Content-rich Network Embedding, KDD 2019."
Grouped 3,411 actors into 3 communities and 1,292 movies into 50 clusters using heterogeneous random walks and Word2Vec embeddings on a bipartite actor-movie network. Designed custom graph-aware metrics for optimal cluster selection and visualized results with t-SNE.
Various Network Science Projects (2021-2022)
A Graph Optimal Transport Python Package
Implementation of GNN - Node embeddings, classification & Link Prediction on CORA & soc-hamsterster dataset
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