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 101–125 of 982 papers

TitleStatusHype
Graph-based prediction of Protein-protein interactions with attributed signed graph embeddingCode1
Graph Contrastive Learning Meets Graph Meta Learning: A Unified Method for Few-shot Node TasksCode1
Class-Imbalanced Learning on Graphs: A SurveyCode1
AutoGCL: Automated Graph Contrastive Learning via Learnable View GeneratorsCode1
A Meta-Learning Approach for Graph Representation Learning in Multi-Task SettingsCode1
Graph-Fraudster: Adversarial Attacks on Graph Neural Network Based Vertical Federated LearningCode1
COSTA: Covariance-Preserving Feature Augmentation for Graph Contrastive LearningCode1
Graph Mixture Density NetworksCode1
Graph Neural Networks in Recommender Systems: A SurveyCode1
Beyond Smoothing: Unsupervised Graph Representation Learning with Edge Heterophily DiscriminatingCode1
CCGL: Contrastive Cascade Graph LearningCode1
Bi-GCN: Binary Graph Convolutional NetworkCode1
An adaptive graph learning method for automated molecular interactions and properties predictionsCode1
Graph Representation Learning for Multi-Task Settings: a Meta-Learning ApproachCode1
GRPE: Relative Positional Encoding for Graph TransformerCode1
Graph Trend Filtering Networks for RecommendationsCode1
Boosting Graph Structure Learning with Dummy NodesCode1
Boost then Convolve: Gradient Boosting Meets Graph Neural NetworksCode1
Large-Scale Representation Learning on Graphs via BootstrappingCode1
Continuous-Time and Multi-Level Graph Representation Learning for Origin-Destination Demand PredictionCode1
An Effective and Efficient Entity Alignment Decoding Algorithm via Third-Order Tensor IsomorphismCode1
Heterogeneous Graph Representation Learning with Relation AwarenessCode1
Hierarchical Graph Representation Learning with Differentiable PoolingCode1
Hierarchical Graph Representation Learning for the Prediction of Drug-Target Binding AffinityCode1
Data Augmentation on Graphs: A Technical SurveyCode1
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Benchmark Results

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