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 51–75 of 982 papers

TitleStatusHype
EchoGLAD: Hierarchical Graph Neural Networks for Left Ventricle Landmark Detection on EchocardiogramsCode1
A Meta-Learning Approach for Graph Representation Learning in Multi-Task SettingsCode1
Edge Representation Learning with HypergraphsCode1
A critical look at the evaluation of GNNs under heterophily: Are we really making progress?Code1
Adversarial Graph DisentanglementCode1
An adaptive graph learning method for automated molecular interactions and properties predictionsCode1
EvolveGCN: Evolving Graph Convolutional Networks for Dynamic GraphsCode1
Expander Graph PropagationCode1
Data Augmentation on Graphs: A Technical SurveyCode1
An Effective and Efficient Entity Alignment Decoding Algorithm via Third-Order Tensor IsomorphismCode1
Fast Graph Learning with Unique Optimal SolutionsCode1
An Open Challenge for Inductive Link Prediction on Knowledge GraphsCode1
Continuous-Time and Multi-Level Graph Representation Learning for Origin-Destination Demand PredictionCode1
Class-Imbalanced Learning on Graphs: A SurveyCode1
COSTA: Covariance-Preserving Feature Augmentation for Graph Contrastive LearningCode1
Decoupling Weighing and Selecting for Integrating Multiple Graph Pre-training TasksCode1
Boost then Convolve: Gradient Boosting Meets Graph Neural NetworksCode1
Boosting Graph Structure Learning with Dummy NodesCode1
Large-Scale Representation Learning on Graphs via BootstrappingCode1
A Representation Learning Framework for Property GraphsCode1
CCGL: Contrastive Cascade Graph LearningCode1
Certifiably Robust Graph Contrastive LearningCode1
Unleashing the Power of Graph Data Augmentation on Covariate Distribution ShiftCode1
A step towards neural genome assemblyCode1
A Structure-Aware Framework for Learning Device Placements on Computation GraphsCode1
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Benchmark Results

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