SOTAVerified

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 AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 751–800 of 982 papers

TitleStatusHype
RMNA: A Neighbor Aggregation-Based Knowledge Graph Representation Learning Model Using Rule MiningCode0
Knowledge Graph Representation Learning using Ordinary Differential Equations—0
Geo-BERT Pre-training Model for Query Rewriting in POI Search—0
InfoGCL: Information-Aware Graph Contrastive Learning—0
Graph Communal Contrastive LearningCode0
Pairwise Half-graph Discrimination: A Simple Graph-level Self-supervised Strategy for Pre-training Graph Neural Networks—0
Tackling the Local Bias in Federated Graph Learning—0
DPGNN: Dual-Perception Graph Neural Network for Representation Learning—0
Residual2Vec: Debiasing graph embedding with random graphsCode0
MGC: A Complex-Valued Graph Convolutional Network for Directed GraphsCode0
Asymmetric Graph Representation Learning—0
GCN-SE: Attention as Explainability for Node Classification in Dynamic Graphs—0
Cycle Representation Learning for Inductive Relation PredictionCode0
Revisiting SVD to generate powerful Node Embeddings for Recommendation Systems—0
Wireless Link Scheduling via Graph Representation Learning: A Comparative Study of Different Supervision LevelsCode0
Graph Representation Learning for Spatial Image Steganalysis—0
Reconstruction for Powerful Graph Representations—0
GLASS: GNN with Labeling Tricks for Subgraph Representation Learning—0
Using Graph Representation Learning with Schema Encoders to Measure the Severity of Depressive Symptoms—0
Towards Feature Overcorrelation in Deeper Graph Neural Networks—0
A Transferable General-Purpose Predictor for Neural Architecture Search—0
SpecTRA: Spectral Transformer for Graph Representation Learning—0
BCDR: Betweenness Centrality-based Distance Resampling for Graph Shortest Distance Embedding—0
Scalable Hierarchical Embeddings of Complex Networks—0
Interrogating Paradigms in Self-supervised Graph Representation Learning—0
EBSD Grain Knowledge Graph Representation Learning for Material Structure-Property Prediction—0
A Deep Latent Space Model for Directed Graph Representation Learning—0
Edge but not Least: Cross-View Graph Pooling—0
Graphine: A Dataset for Graph-aware Terminology Definition GenerationCode0
X-GOAL: Multiplex Heterogeneous Graph Prototypical Contrastive Learning—0
Pointspectrum: Equivariance Meets Laplacian Filtering for Graph Representation Learning—0
Graph-based Incident Aggregation for Large-Scale Online Service SystemsCode0
ETA Prediction with Graph Neural Networks in Google Maps—0
HopfE: Knowledge Graph Representation Learning using Inverse Hopf FibrationsCode0
Self-supervised Consensus Representation Learning for Attributed GraphCode0
Localized Graph Collaborative Filtering—0
DySR: A Dynamic Representation Learning and Aligning based Model for Service Bundle Recommendation—0
Hyperparameter-free and Explainable Whole Graph EmbeddingCode0
Graph Neural Networks With Lifting-based Adaptive Graph Wavelets—0
JCapsR: 一种联合胶囊神经网络的藏语知识图谱表示学习模型(JCapsR: A Joint Capsule Neural Network for Tibetan Knowledge Graph Representation Learning)—0
Local2Global: Scaling global representation learning on graphs via local trainingCode0
Graph Representation Learning on Tissue-Specific Multi-Omics—0
Data Considerations in Graph Representation Learning for Supply Chain Networks—0
Large-scale graph representation learning with very deep GNNs and self-supervision—0
WikiGraphs: A Wikipedia Text - Knowledge Graph Paired DatasetCode0
Graph Representation Learning for Road Type ClassificationCode0
MugRep: A Multi-Task Hierarchical Graph Representation Learning Framework for Real Estate Appraisal—0
Multi-Level Graph Contrastive Learning—0
HCGR: Hyperbolic Contrastive Graph Representation Learning for Session-based Recommendation—0
Multi-modal Graph Learning for Disease Prediction—0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1Pi-net-linearError (mm)0.47—Unverified