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 176–200 of 982 papers

TitleStatusHype
COSTA: Covariance-Preserving Feature Augmentation for Graph Contrastive LearningCode1
Generalized Graph Prompt: Toward a Unification of Pre-Training and Downstream Tasks on GraphsCode1
M2GRL: A Multi-task Multi-view Graph Representation Learning Framework for Web-scale Recommender SystemsCode1
A Graph is Worth K Words: Euclideanizing Graph using Pure TransformerCode1
MAGNET: Multi-Label Text Classification using Attention-based Graph Neural NetworkCode1
Fast Graph Representation Learning with PyTorch GeometricCode1
MHNF: Multi-hop Heterogeneous Neighborhood information Fusion graph representation learningCode1
Data Augmentation on Graphs: A Technical SurveyCode1
FTM: A Frame-level Timeline Modeling Method for Temporal Graph Representation LearningCode1
Motif-based Graph Representation Learning with Application to Chemical MoleculesCode1
Multi-dimensional Edge-based Audio Event Relational Graph Representation Learning for Acoustic Scene ClassificationCode1
GCC: Graph Contrastive Coding for Graph Neural Network Pre-TrainingCode1
GCondenser: Benchmarking Graph CondensationCode1
Audio Event-Relational Graph Representation Learning for Acoustic Scene ClassificationCode1
Multi-view Tensor Graph Neural Networks Through Reinforced AggregationCode1
Domain Adversarial Spatial-Temporal Network: A Transferable Framework for Short-term Traffic Forecasting across CitiesCode1
RELIEF: Reinforcement Learning Empowered Graph Feature Prompt TuningCode1
Geometry-Complete Perceptron Networks for 3D Molecular GraphsCode1
Information Obfuscation of Graph Neural NetworksCode1
A Large-Scale Database for Graph Representation LearningCode1
Deep Graph Contrastive Representation LearningCode1
OQM9HK: A Large-Scale Graph Dataset for Machine Learning in Materials ScienceCode1
Deep Graph Mapper: Seeing Graphs through the Neural LensCode1
Deep Graph Representation Learning and Optimization for Influence MaximizationCode1
Graphonomy: Universal Image Parsing via Graph Reasoning and TransferCode1
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Benchmark Results

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