A collection of important graph embedding, classification and representation learning papers with implementations.
A scikit-learn compatible library for graph kernels
#计算机科学#This repository contains the "tensorflow" implementation of our paper "graph2vec: Learning distributed representations of graphs".
#计算机科学#A python package for graph kernels, graph edit distances, and graph pre-image problem.
A convolutional neural network for graph classification in PyTorch
A Parallel Graphlet Decomposition Library for Large Graphs
#计算机科学#Code and data for the paper 'Classifying Graphs as Images with Convolutional Neural Networks' (new title: 'Graph Classification with 2D Convolutional Neural Networks')
#计算机科学#A Persistent Weisfeiler–Lehman Procedure for Graph Classification
Deriving Neural Architectures from Sequence and Graph Kernels
Dataset for testing graph classification algorithms, such as Graph Kernels and Graph Neural Networks.
A collection of graph classification methods
#计算机科学#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"
#计算机科学#This repository contains the TensorFlow implemtation of subgraph2vec (KDD MLG 2016) paper
Official code for Fisher information embedding for node and graph learning (ICML 2023)
#计算机科学#Source code for our IEEE ICDM 2016 paper "Faster Kernels for Graphs with Continuous Attributes".
#数据仓库#A package for downloading and working with graph datasets
Isotropic Gaussian Processs on Finite Spaces of Graphs (AISTATS 2023)