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

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Showing 76–100 of 982 papers

TitleStatusHype
Adversarial Graph DisentanglementCode1
Continuous-Time and Multi-Level Graph Representation Learning for Origin-Destination Demand PredictionCode1
A critical look at the evaluation of GNNs under heterophily: Are we really making progress?Code1
A Fair Comparison of Graph Neural Networks for Graph ClassificationCode1
DropMessage: Unifying Random Dropping for Graph Neural NetworksCode1
A Generalization of ViT/MLP-Mixer to GraphsCode1
Data Augmentation on Graphs: A Technical SurveyCode1
A Representation Learning Framework for Property GraphsCode1
Edge-aware Graph Representation Learning and Reasoning for Face ParsingCode1
A Gentle Introduction to Deep Learning for GraphsCode1
Unleashing the Power of Graph Data Augmentation on Covariate Distribution ShiftCode1
Bi-GCN: Binary Graph Convolutional NetworkCode1
Enhancing Graph Representation Learning with Localized Topological FeaturesCode1
A Graph is Worth K Words: Euclideanizing Graph using Pure TransformerCode1
EvolveGCN: Evolving Graph Convolutional Networks for Dynamic GraphsCode1
Decoupling Weighing and Selecting for Integrating Multiple Graph Pre-training TasksCode1
CCGL: Contrastive Cascade Graph LearningCode1
Exploiting Edge-Oriented Reasoning for 3D Point-based Scene Graph AnalysisCode1
Audio Event-Relational Graph Representation Learning for Acoustic Scene ClassificationCode1
RELIEF: Reinforcement Learning Empowered Graph Feature Prompt TuningCode1
Boosting Graph Structure Learning with Dummy NodesCode1
A Large-Scale Database for Graph Representation LearningCode1
Large-Scale Representation Learning on Graphs via BootstrappingCode1
Algorithm and System Co-design for Efficient Subgraph-based Graph Representation LearningCode1
Catastrophic Forgetting in Deep Graph Networks: an Introductory Benchmark for Graph ClassificationCode1
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Benchmark Results

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