Feature Expansion for Graph Neural Networks [ICML-2023]
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Updated
Jul 2, 2024 - Python
Feature Expansion for Graph Neural Networks [ICML-2023]
The SINr approach to train interpretable word and graph embeddings
Karate Club: An API Oriented Open-source Python Framework for Unsupervised Learning on Graphs (CIKM 2020)
PyTorch Geometric Temporal: Spatiotemporal Signal Processing with Neural Machine Learning Models (CIKM 2021)
Convierte tus proyectos de Node.js en ejecutables ( .exe )
Do Transformers Really Perform Bad for Graph Representation? [NIPS-2021]
This repository contains the implementation of some of the popular Graph Neural Networks (GNNs) using PyTorch Geometric to solve node classification tasks.
SimGNN: A Neural Network Approach to Fast Graph Similarity Computation [WSDM-2019]
A repository of pretty cool datasets that I collected for network science and machine learning research.
Little Ball of Fur - A graph sampling extension library for NetworKit and NetworkX (CIKM 2020)
Learning Structural Node Representations using Graph Kernels
CS224W-Machine learning with Graph by Stanford
Data and code repository from "DINE: Dimensional Interpretability of Node Embeddings"
A Pytorch implementation of "Splitter: Learning Node Representations that Capture Multiple Social Contexts" (WWW 2019).
Official implementation of "NESS: Node Embeddings from Static Subgraphs"
Node embedding technique based on Masked Language Model.
PyTorch Implementation and Explanation of Graph Representation Learning papers: DeepWalk, GCN, GraphSAGE, ChebNet & GAT.
The reference implementation of FEATHER from the CIKM '20 paper "Characteristic Functions on Graphs: Birds of a Feather, from Statistical Descriptors to Parametric Models".
A PyTorch Implementation of "SINE: Scalable Incomplete Network Embedding" (ICDM 2018).
A lightweight implementation of Walklets from "Don't Walk Skip! Online Learning of Multi-scale Network Embeddings" (ASONAM 2017).
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