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 551–575 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 Survey—0
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 Learning—0
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 Measurements—0
Recipe for a General, Powerful, Scalable Graph TransformerCode2
KQGC: Knowledge Graph Embedding with Smoothing Effects of Graph Convolutions for Recommendation—0
Revisiting the role of heterophily in graph representation learning: An edge classification perspective—0
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 Recommendation—0
Embodied-Symbolic Contrastive Graph Self-Supervised Learning for Molecular Graphs—0
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 Learning—0
Show:102550
← PrevPage 23 of 40Next →

Benchmark Results

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