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 801–850 of 982 papers

TitleStatusHype
Recursive Neighborhood Pooling for Graph Representation Learning—0
Beyond COVID-19 Diagnosis: Prognosis with Hierarchical Graph Representation Learning—0
GL-Disen: Global-Local disentanglement for unsupervised learning of graph-level representations—0
xERTE: Explainable Reasoning on Temporal Knowledge Graphs for Forecasting Future LinksCode1
Deep Graph Generators: A Survey—0
Deep Multi-attribute Graph Representation Learning on Protein Structures—0
Hop-Hop Relation-aware Graph Neural Networks—0
Biomedical Knowledge Graph Refinement and Completion using Graph Representation Learning and Top-K Similarity Measure—0
A Meta-Learning Approach for Graph Representation Learning in Multi-Task SettingsCode1
Decimated Framelet System on Graphs and Fast G-Framelet TransformsCode0
Pair-view Unsupervised Graph Representation Learning—0
CommPOOL: An Interpretable Graph Pooling Framework for Hierarchical Graph Representation Learning—0
Graph Mixture Density NetworksCode1
Unsupervised Adversarially-Robust Representation Learning on Graphs—0
A Survey on Heterogeneous Graph Embedding: Methods, Techniques, Applications and Sources—0
A Data-Driven Study of Commonsense Knowledge using the ConceptNet Knowledge Base—0
GL-Coarsener: A Graph representation learning framework to construct coarse grid hierarchy for AMG solversCode0
Node Similarity Preserving Graph Convolutional NetworksCode1
A Large-Scale Database for Graph Representation LearningCode1
Distill2Vec: Dynamic Graph Representation Learning with Knowledge DistillationCode0
EGAD: Evolving Graph Representation Learning with Self-Attention and Knowledge Distillation for Live Video Streaming EventsCode0
VStreamDRLS: Dynamic Graph Representation Learning with Self-Attention for Enterprise Distributed Video Streaming SolutionsCode0
A step towards neural genome assemblyCode1
Relation-weighted Link Prediction for Disease Gene Identification—0
Self-supervised Graph Representation Learning via Bootstrapping—0
Massively Parallel Graph Drawing and Representation LearningCode0
Graph Neural Networks in Recommender Systems: A SurveyCode1
PersGNN: Applying Topological Data Analysis and Geometric Deep Learning to Structure-Based Protein Function Prediction—0
When Contrastive Learning Meets Active Learning: A Novel Graph Active Learning Paradigm with Self-Supervision—0
Handling Missing Data with Graph Representation LearningCode1
GripNet: Graph Information Propagation on Supergraph for Heterogeneous GraphsCode1
Geometric Scattering Attention NetworksCode0
Graph Contrastive Learning with Adaptive AugmentationCode1
Personalised Meta-path Generation for Heterogeneous GNNsCode1
XLVIN: eXecuted Latent Value Iteration Nets—0
Distributed Representations of Entities in Open-World Knowledge Graphs—0
Bi-GCN: Binary Graph Convolutional NetworkCode1
Towards Expressive Graph RepresentationCode0
Multivariate Time Series Classification with Hierarchical Variational Graph Pooling—0
Reward Propagation Using Graph Convolutional NetworksCode1
Disentangle-based Continual Graph Representation LearningCode1
NodeSig: Binary Node Embeddings via Random Walk Diffusion—0
Multi-hop Attention Graph Neural NetworkCode1
Information Obfuscation of Graph Neural NetworksCode1
Sub-graph Contrast for Scalable Self-Supervised Graph Representation LearningCode1
div2vec: Diversity-Emphasized Node Embedding—0
Graph InfoClust: Leveraging cluster-level node information for unsupervised graph representation learningCode1
Polyp-artifact relationship analysis using graph inductive learned representations—0
GraphNorm: A Principled Approach to Accelerating Graph Neural Network TrainingCode1
Online Disease Self-diagnosis with Inductive Heterogeneous Graph Convolutional Networks—0
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Benchmark Results

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