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 1–50 of 982 papers

TitleStatusHype
ROLAND: Graph Learning Framework for Dynamic GraphsCode3
CogDL: A Comprehensive Library for Graph Deep LearningCode2
Dynamic Graph Representation with Knowledge-aware Attention for Histopathology Whole Slide Image AnalysisCode2
Graph Domain Adaptation: Challenges, Progress and ProspectsCode2
Effect of Choosing Loss Function when Using T-batching for Representation Learning on Dynamic NetworksCode2
Towards Relation-centered Pooling and Convolution for Heterogeneous Graph Learning NetworksCode2
Graph4Rec: A Universal Toolkit with Graph Neural Networks for Recommender SystemsCode2
Graph Neural Networks for Natural Language Processing: A SurveyCode2
Tractable Probabilistic Graph Representation Learning with Graph-Induced Sum-Product NetworksCode2
NeuralKG-ind: A Python Library for Inductive Knowledge Graph Representation LearningCode2
Do Transformers Really Perform Bad for Graph Representation?Code2
Structure-Aware Transformer for Graph Representation LearningCode2
Explanation-Preserving Augmentation for Semi-Supervised Graph Representation LearningCode2
LambdaKG: A Library for Pre-trained Language Model-Based Knowledge Graph EmbeddingsCode2
A Survey of Pretraining on Graphs: Taxonomy, Methods, and ApplicationsCode2
Harnessing Explanations: LLM-to-LM Interpreter for Enhanced Text-Attributed Graph Representation LearningCode2
A Survey on Knowledge Graphs: Representation, Acquisition and ApplicationsCode2
Recipe for a General, Powerful, Scalable Graph TransformerCode2
VideoSAGE: Video Summarization with Graph Representation LearningCode2
Does Graph Distillation See Like Vision Dataset Counterpart?Code1
Disentangle-based Continual Graph Representation LearningCode1
Does Invariant Graph Learning via Environment Augmentation Learn Invariance?Code1
Deep Graph Contrastive Representation LearningCode1
Deep Graph Representation Learning and Optimization for Influence MaximizationCode1
An Open Challenge for Inductive Link Prediction on Knowledge GraphsCode1
Deep Graph Mapper: Seeing Graphs through the Neural LensCode1
An Effective and Efficient Entity Alignment Decoding Algorithm via Third-Order Tensor IsomorphismCode1
Multi-hop Attention Graph Neural NetworkCode1
Distance Encoding: Design Provably More Powerful Neural Networks for Graph Representation LearningCode1
Distribution-Aware Graph Representation Learning for Transient Stability Assessment of Power SystemCode1
An adaptive graph learning method for automated molecular interactions and properties predictionsCode1
Decoupling Weighing and Selecting for Integrating Multiple Graph Pre-training TasksCode1
DiffKG: Knowledge Graph Diffusion Model for RecommendationCode1
Domain Adversarial Spatial-Temporal Network: A Transferable Framework for Short-term Traffic Forecasting across CitiesCode1
A Meta-Learning Approach for Graph Representation Learning in Multi-Task SettingsCode1
Certifiably Robust Graph Contrastive LearningCode1
Continuous-Time and Multi-Level Graph Representation Learning for Origin-Destination Demand PredictionCode1
Large-Scale Representation Learning on Graphs via BootstrappingCode1
TransGNN: Harnessing the Collaborative Power of Transformers and Graph Neural Networks for Recommender SystemsCode1
A Generalization of ViT/MLP-Mixer to GraphsCode1
A Fair Comparison of Graph Neural Networks for Graph ClassificationCode1
A Gentle Introduction to Deep Learning for GraphsCode1
CCGL: Contrastive Cascade Graph LearningCode1
A Graph is Worth K Words: Euclideanizing Graph using Pure TransformerCode1
Boost then Convolve: Gradient Boosting Meets Graph Neural NetworksCode1
Class-Imbalanced Learning on Graphs: A SurveyCode1
RELIEF: Reinforcement Learning Empowered Graph Feature Prompt TuningCode1
A Large-Scale Database for Graph Representation LearningCode1
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