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benchmark-benchmarking-gnns

Repository for benchmarking graph neural networks

dagnn

A graph neural network tailored to directed acyclic graphs that outperforms conventional GNNs by leveraging the partial order as strong inductive bias besides other suitable architectural features.

dgnn-pytorch

Unofficial PyTorch implementation of the CVPR'19 paper "Skeleton-Based Action Recognition with Directed Graph Neural Networks".

digcl

The PyTorch implementation of Directed Graph Contrastive Learning (DiGCL), NeurIPS-2021

digcn

Implement of DiGCN, NeurIPS-2020

ec-bestiary

A bestiary of evolutionary, swarm and other metaphor-based algorithms

gcn

Implementation of Graph Convolutional Networks in TensorFlow

geom_gcn_pytorch_implementation

Geom_GCN re-implementation using only pytorch. ( Not using DGL)

gnn-comparison

Official Repository of "A Fair Comparison of Graph Neural Networks for Graph Classification", ICLR 2020

gnnrank

Official code for the ICML2022 paper -- GNNRank: Learning Global Rankings from Pairwise Comparisons via Directed Graph Neural Networks

gprgnn

graphnas

This directory contains code necessary to run the GraphNAS algorithm.

graphsage

Representation learning on large graphs using stochastic graph convolutions.

graphsaint

[ICLR 2020; IPDPS 2019] Fast and accurate minibatch training for deep GNNs and large graphs (GraphSAINT: Graph Sampling Based Inductive Learning Method).

graphsha

"GraphSHA: Synthesizing Harder Samples for Class-Imbalanced Node Classification" in KDD'23

graphsha_share

Share with Supervisors

h2gcn

Boost learning for GNNs from the graph structure under challenging heterophily settings. (NeurIPS'20)

heteroge-graph

hgcl

[WSDM'2023] "HGCL: Heterogeneous Graph Contrastive Learning for Recommendation"

kernelgcn

Codes for NIPS 2019 Paper: Rethinking Kernel Methods for Node Representation Learning on Graphs

konect-extr

Network dataset extraction library – part of the KONECT project by Jérôme Kunegis, University of Namur

lisa

Code for Mind the Label Shift of Augmentation-based Graph OOD generalization (LiSA) in CVPR 2023. LiSA is a model-agnostic Graph OOD framework.

magnet

MagNet graph convolutional network

magnet0

magnetmain

msgnn

Official code for the LoG2022 paper -- MSGNN: A Spectral Graph Neural Network Based on a Novel Magnetic Signed Laplacian.

nosmog

Code & data for ICLR'23 Spotlight paper "Learning MLPs on Graphs: A Unified View of Effectiveness, Robustness, and Efficiency".

over-smoothing

Code for Graph Neural Networks Exponentially Lose Expressive Power for Node Classification.

pgnns

[ICML 2022] pGNN, p-Laplacian Based Graph Neural Networks

posts

A repository for code accompanying my Medium posts.