graph-kernels

ysig/GraKeL

A scikit-learn compatible library for graph kernels

annamalai-nr/graph2vec_tf

This repository contains the "tensorflow" implementation of our paper "graph2vec: Learning distributed representations of graphs".

jajupmochi/graphkit-learn

A python package for graph kernels, graph edit distances, and graph pre-image problem.

BorgwardtLab/GraphKernels

A package for computing Graph Kernels

giannisnik/cnn-graph-classification

A convolutional neural network for graph classification in PyTorch

nkahmed/PGD

A Parallel Graphlet Decomposition Library for Large Graphs

Tixierae/graph_2D_CNN

Code and data for the paper 'Classifying Graphs as Images with Convolutional Neural Networks' (new title: 'Graph Classification with 2D Convolutional Neural Networks')

taolei87/icml17_knn

Deriving Neural Architectures from Sequence and Graph Kernels

BorgwardtLab/P-WL

A Persistent Weisfeiler–Lehman Procedure for Graph Classification

annamalai-nr/subgraph2vec_gensim

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"

sunfanyunn/graph-classification

A collection of graph classification methods

annamalai-nr/subgraph2vec_tf

This repository contains the TensorFlow implemtation of subgraph2vec (KDD MLG 2016) paper

SAG-KeLP/kelp-additional-kernels

BorgwardtLab/fisher_information_embedding

Official code for Fisher information embedding for node and graph learning (ICML 2023)

giannisnik/message_passing_graph_kernels

chrsmrrs/hashgraphkernel

Source code for our IEEE ICDM 2016 paper "Faster Kernels for Graphs with Continuous Attributes".

simonschoelly/GraphDatasets.jl

A package for downloading and working with graph datasets

IBM/graph_space_gps

Isotropic Gaussian Processs on Finite Spaces of Graphs (AISTATS 2023)

Pseudomanifold/enchiridion-tda

An enchiridion for instructing mortals in the hidden arts of topological data analysis

ethiy/evaluation_building_models_learning

Semantics aware quality evaluation of building 3D models: a learning approach

simonschoelly/GraphKernels.jl

A Julia package for kernel functions on graphs

ChNousias/graph-classification-thesis

Classification Task on Graphs using Graph Neural Networks and Graph Kernels - Thesis Project

disi-unibo-nlp/ddegk

Implementation of Deep Divergence Event Graph Kernels

jgurakuqi/graph-kernels-and-manifold-svm

This project aims to compare the performance obtained using a linear Support Vector Machine model whose data was first processed through a Shortest Path kernel with the same SVM, this time with data also processed by two alternative Manifold Learning techniques: Isomap and Spectral Embedding.

thejkane/AGM

elaaj/weisfeiler-and-manifold-techniques-svm

The goal here is to use a graph kernel and a manifold learning technique in conjunction with Support Vector Machines to enhance the SVM classification.

nkanak/cordkel

Shall I work with them? A ‘knowledge graph’-based approach for predicting future research collaborations