A collection of important graph embedding, classification and representation learning papers with implementations.
翻译 - 一系列重要的图形嵌入，分类和表示学习论文以及实现。
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
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)
An enchiridion for instructing mortals in the hidden arts of topological data analysis