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

Showing 551600 of 982 papers

TitleStatusHype
NAFS: A Simple yet Tough-to-beat Baseline for Graph Representation LearningCode0
Taxonomy of Benchmarks in Graph Representation LearningCode1
COSTA: Covariance-Preserving Feature Augmentation for Graph Contrastive LearningCode1
Metric Based Few-Shot Graph ClassificationCode1
Learning with Capsules: A Survey0
A knowledge graph representation learning approach to predict novel kinase-substrate interactionsCode0
Rethinking and Scaling Up Graph Contrastive Learning: An Extremely Efficient Approach with Group DiscriminationCode1
KPGT: Knowledge-Guided Pre-training of Graph Transformer for Molecular Property PredictionCode1
An Empirical Study of Retrieval-enhanced Graph Neural NetworksCode0
Omni-Granular Ego-Semantic Propagation for Self-Supervised Graph Representation Learning0
Embedding Graphs on Grassmann ManifoldCode0
Dynamic Graph Learning Based on Hierarchical Memory for Origin-Destination Demand PredictionCode1
GraphPMU: Event Clustering via Graph Representation Learning Using Locationally-Scarce Distribution-Level Fundamental and Harmonic PMU Measurements0
Recipe for a General, Powerful, Scalable Graph TransformerCode2
KQGC: Knowledge Graph Embedding with Smoothing Effects of Graph Convolutions for Recommendation0
Revisiting the role of heterophily in graph representation learning: An edge classification perspective0
Relphormer: Relational Graph Transformer for Knowledge Graph RepresentationsCode1
Are Graph Representation Learning Methods Robust to Graph Sparsity and Asymmetric Node Information?0
Poincaré Heterogeneous Graph Neural Networks for Sequential Recommendation0
Embodied-Symbolic Contrastive Graph Self-Supervised Learning for Molecular Graphs0
Distribution-Aware Graph Representation Learning for Transient Stability Assessment of Power SystemCode1
Using Constraint Programming and Graph Representation Learning for Generating Interpretable Cloud Security PoliciesCode0
An Effective and Efficient Entity Alignment Decoding Algorithm via Third-Order Tensor IsomorphismCode1
GTNet: A Tree-Based Deep Graph Learning ArchitectureCode0
LiftPool: Lifting-based Graph Pooling for Hierarchical Graph Representation Learning0
End-to-end Mapping in Heterogeneous Systems Using Graph Representation Learning0
All-optical graph representation learning using integrated diffractive photonic computing units0
DropMessage: Unifying Random Dropping for Graph Neural NetworksCode1
Simplicial Attention NetworksCode1
A Hierarchical Block Distance Model for Ultra Low-Dimensional Graph RepresentationsCode0
A Survey on Graph Representation Learning Methods0
On Understanding and Mitigating the Dimensional Collapse of Graph Contrastive Learning: a Non-Maximum Removal Approach0
Hierarchical Graph Representation Learning for the Prediction of Drug-Target Binding AffinityCode1
Explainability in Graph Neural Networks: An Experimental Survey0
Few-Shot Learning on Graphs0
Graph Representation Learning with Individualization and Refinement0
Graph Representation Learning for Popularity Prediction Problem: A Survey0
Multi-modal Graph Learning for Disease PredictionCode1
Flurry: a Fast Framework for Reproducible Multi-layered Provenance Graph Representation Learning0
Graph Representation Learning Beyond Node and HomophilyCode0
An Open Challenge for Inductive Link Prediction on Knowledge GraphsCode1
Understanding microbiome dynamics via interpretable graph representation learningCode0
Algorithm and System Co-design for Efficient Subgraph-based Graph Representation LearningCode1
Distribution Preserving Graph Representation Learning0
Sign and Basis Invariant Networks for Spectral Graph Representation LearningCode1
Message passing all the way up0
Interactive Visual Pattern Search on Graph Data via Graph Representation Learning0
A Survey of Pretraining on Graphs: Taxonomy, Methods, and ApplicationsCode2
Adversarial Graph Contrastive Learning with Information RegularizationCode0
Geometric Graph Representation Learning via Maximizing Rate Reduction0
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Benchmark Results

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