Graph Representation Learning

The goal of Graph Representation Learning is to construct a set of features (‘embeddings’) representing the structure of the graph and the data thereon. We can distinguish among Node-wise embeddings, representing each node of the graph, Edge-wise embeddings, representing each edge in the graph, and Graph-wise embeddings representing the graph as a whole.

Source: SIGN: Scalable Inception Graph Neural Networks

Papers

Recently Added Most Hyped Most Active Needs Verification Most Verified

Showing 326–350 of 982 papers

Title	Date	Tasks	Status	Score
Calibrating and Improving Graph Contrastive Learning	Jan 27, 2021	Contrastive LearningGraph Clustering	CodeCode Available	5
Iso-CapsNet: Isomorphic Capsule Network for Brain Graph Representation Learning	Jun 27, 2022	Graph Representation LearningRepresentation Learning	CodeCode Available	5
Imbalanced Graph Classification with Multi-scale Oversampling Graph Neural Networks	May 8, 2024	Graph ClassificationGraph Learning	CodeCode Available	5
Adaptive Graph Representation Learning for Video Person Re-identification	Sep 5, 2019	Graph Representation LearningPerson Re-Identification	CodeCode Available	5
Hyperparameter-free and Explainable Whole Graph Embedding	Aug 4, 2021	Graph ClassificationGraph Embedding	CodeCode Available	5
Contrastive Learning Meets Pseudo-label-assisted Mixup Augmentation: A Comprehensive Graph Representation Framework from Local to Global	Jan 30, 2025	Contrastive LearningGraph Representation Learning	CodeCode Available	5
GEFL: Extended Filtration Learning for Graph Classification	Jun 4, 2024	ClassificationGraph Classification	CodeCode Available	5
Hyperbolic Geometric Graph Representation Learning for Hierarchy-imbalance Node Classification	Apr 11, 2023	Graph Representation LearningNode Classification	CodeCode Available	5
IsoNN: Isomorphic Neural Network for Graph Representation Learning and Classification	Jul 22, 2019	ClassificationGeneral Classification	CodeCode Available	5
Hierarchical Multi-Relational Graph Representation Learning for Large-Scale Prediction of Drug-Drug Interactions	Feb 28, 2024	Graph Representation LearningRepresentation Learning	CodeCode Available	5
Hierarchical Topology Isomorphism Expertise Embedded Graph Contrastive Learning	Dec 21, 2023	Contrastive LearningGraph Representation Learning	CodeCode Available	5
Connector 0.5: A unified framework for graph representation learning	Apr 25, 2023	Graph EmbeddingGraph Generation	CodeCode Available	5
From ChebNet to ChebGibbsNet	Dec 2, 2024	Graph Representation LearningNode Classification	CodeCode Available	5
Hierarchical and Unsupervised Graph Representation Learning with Loukas's Coarsening	Jul 7, 2020	Graph Representation LearningRepresentation Learning	CodeCode Available	5
Hyperbolic Neural Networks	May 23, 2018	Graph Representation LearningNatural Language Inference	CodeCode Available	5
HopfE: Knowledge Graph Representation Learning using Inverse Hopf Fibrations	Aug 12, 2021	Graph EmbeddingGraph Representation Learning	CodeCode Available	5
Hyper-SAGNN: a self-attention based graph neural network for hypergraphs	Nov 6, 2019	Graph Neural NetworkGraph Representation Learning	CodeCode Available	5
Frameless Graph Knowledge Distillation	Jul 13, 2023	Graph Representation LearningKnowledge Distillation	CodeCode Available	5
ConCur: Self-supervised graph representation based on contrastive learning with curriculum negative sampling	Sep 1, 2023	Contrastive LearningGraph Representation Learning	CodeCode Available	5
Geometric Scattering Attention Networks	Oct 28, 2020	Graph Representation LearningNode Classification	CodeCode Available	5
Het-node2vec: second order random walk sampling for heterogeneous multigraphs embedding	Jan 5, 2021	Graph Representation LearningRepresentation Learning	CodeCode Available	5
Heterogeneous Deep Graph Infomax	Nov 19, 2019	ClassificationClustering	CodeCode Available	5
Accelerating Dynamic Network Embedding with Billions of Parameter Updates to Milliseconds	Jun 15, 2023	Graph ReconstructionGraph Representation Learning	CodeCode Available	5
Comprehensive Analysis of Negative Sampling in Knowledge Graph Representation Learning	Jun 21, 2022	Graph EmbeddingGraph Representation Learning	CodeCode Available	5
Harnessing Collective Structure Knowledge in Data Augmentation for Graph Neural Networks	May 17, 2024	Anomaly DetectionData Augmentation	CodeCode Available	5

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Benchmark Results

#	Model	Metric	Claimed	Verified	Status
1	Pi-net-linear	Error (mm)	0.47	—	Unverified