A collection of important graph embedding, classification and representation learning papers with implementations.
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Updated
Mar 18, 2023 - Python
A collection of important graph embedding, classification and representation learning papers with implementations.
A scikit-learn compatible library for graph kernels
A package for computing Graph Kernels
This repository contains the "tensorflow" implementation of our paper "graph2vec: Learning distributed representations of graphs".
A Parallel Graphlet Decomposition Library for Large Graphs
Code and data for the paper 'Classifying Graphs as Images with Convolutional Neural Networks' (new title: 'Graph Classification with 2D Convolutional Neural Networks')
A convolutional neural network for graph classification in PyTorch
A python package for graph kernels, graph edit distances, and graph pre-image problem.
Contains the code (and working vm setup) for our KDD MLG 2016 paper titled: "subgraph2vec: Learning Distributed Representations of Rooted Sub-graphs from Large Graphs"
Deriving Neural Architectures from Sequence and Graph Kernels
A Persistent Weisfeiler–Lehman Procedure for Graph Classification
This repository contains the TensorFlow implemtation of subgraph2vec (KDD MLG 2016) paper
Source code for our IEEE ICDM 2016 paper "Faster Kernels for Graphs with Continuous Attributes".
A collection of graph classification methods
Isotropic Gaussian Processs on Finite Spaces of Graphs (AISTATS 2023)
Classification Task on Graphs using Graph Neural Networks and Graph Kernels - Thesis Project
An enchiridion for instructing mortals in the hidden arts of topological data analysis
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