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 151–175 of 982 papers

TitleStatusHype
Exploring the Role of Node Diversity in Directed Graph Representation LearningCode0
Your Graph Recommender is Provably a Single-view Graph Contrastive Learning—0
PolyFormer: Scalable Node-wise Filters via Polynomial Graph TransformerCode0
HHGT: Hierarchical Heterogeneous Graph Transformer for Heterogeneous Graph Representation Learning—0
Unsupervised Graph Representation Learning with Inductive Shallow Node EmbeddingCode0
The Heterophilic Graph Learning Handbook: Benchmarks, Models, Theoretical Analysis, Applications and Challenges—0
Edge Graph Intelligence: Reciprocally Empowering Edge Networks with Graph Intelligence—0
Differential Encoding for Improved Representation Learning over Graphs—0
Heterogeneous Graph Contrastive Learning with Spectral Augmentation—0
Inference of Sequential Patterns for Neural Message Passing in Temporal Graphs—0
Harvesting Efficient On-Demand Order Pooling from Skilled Couriers: Enhancing Graph Representation Learning for Refining Real-time Many-to-One Assignments—0
Graph Representation Learning Strategies for Omics Data: A Case Study on Parkinson's Disease—0
RobGC: Towards Robust Graph Condensation—0
Effective Edge-wise Representation Learning in Edge-Attributed Bipartite Graphs—0
A Scalable and Effective Alternative to Graph Transformers—0
A Unified Graph Selective Prompt Learning for Graph Neural Networks—0
OLGA: One-cLass Graph AutoencoderCode0
Introducing Diminutive Causal Structure into Graph Representation Learning—0
Learning Long Range Dependencies on Graphs via Random WalksCode1
Predicting Genetic Mutation from Whole Slide Images via Biomedical-Linguistic Knowledge Enhanced Multi-label ClassificationCode0
GEFL: Extended Filtration Learning for Graph ClassificationCode0
Enhancing Fairness in Unsupervised Graph Anomaly Detection through DisentanglementCode0
Know Your Neighborhood: General and Zero-Shot Capable Binary Function Search Powered by Call GraphletsCode0
Augmentation-based Unsupervised Cross-Domain Functional MRI Adaptation for Major Depressive Disorder Identification—0
Graph External Attention Enhanced TransformerCode1
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Benchmark Results

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