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

Recently AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 901–950 of 982 papers

TitleStatusHype
Wide-AdGraph: Detecting Ad Trackers with a Wide Dependency Chain GraphCode0
MxPool: Multiplex Pooling for Hierarchical Graph Representation Learning—0
Graph Representation Learning via Ladder Gamma Variational AutoencodersCode0
Gossip and Attend: Context-Sensitive Graph Representation LearningCode0
SAC: Accelerating and Structuring Self-Attention via Sparse Adaptive Connection—0
Unsupervised Hierarchical Graph Representation Learning by Mutual Information MaximizationCode0
Learning by Sampling and Compressing: Efficient Graph Representation Learning with Extremely Limited Annotations—0
Learning to Hash with Graph Neural Networks for Recommender Systems—0
Self-Supervised Graph Representation Learning via Global Context Prediction—0
Semiparametric Nonlinear Bipartite Graph Representation Learning with Provable Guarantees—0
Graph Representation Learning for Merchant Incentive Optimization in Mobile Payment Marketing—0
Dual Graph Representation Learning—0
The Power of Graph Convolutional Networks to Distinguish Random Graph Models: Short Version—0
Fake News Detection on News-Oriented Heterogeneous Information Networks through Hierarchical Graph Attention—0
Towards Graph Representation Learning in Emergent Communication—0
Get Rid of Suspended Animation Problem: Deep Diffusive Neural Network on Graph Semi-Supervised ClassificationCode0
Graph Ordering: Towards the Optimal by Learning—0
Robust Graph Representation Learning via Neural SparsificationCode0
An Attention-based Graph Neural Network for Heterogeneous Structural LearningCode0
Bridging the Gap between Community and Node Representations: Graph Embedding via Community DetectionCode0
Multi-Channel Graph Convolutional Networks—0
3D Hand Pose Estimation via Regularized Graph Representation Learning—0
Distribution-induced Bidirectional Generative Adversarial Network for Graph Representation LearningCode0
On Node Features for Graph Neural Networks—0
Heterogeneous Deep Graph InfomaxCode0
GraLSP: Graph Neural Networks with Local Structural Patterns—0
Graph Transformer for Graph-to-Sequence LearningCode0
Graph Representation Learning via Multi-task Knowledge Distillation—0
Hyper-SAGNN: a self-attention based graph neural network for hypergraphsCode0
Is Performance of Scholars Correlated to Their Research Collaboration Patterns?Code0
GraphAIR: Graph Representation Learning with Neighborhood Aggregation and InteractionCode0
Fundamental Limits of Deep Graph Convolutional Networks—0
Graph Representation learning for Audio & Music genre Classification—0
Decoupling feature propagation from the design of graph auto-encoders—0
Relational Graph Representation Learning for Open-Domain Question Answering—0
Disentangling Interpretable Generative Parameters of Random and Real-World Graphs—0
On the Interpretability and Evaluation of Graph Representation Learning—0
Rethinking Kernel Methods for Node Representation Learning on GraphsCode0
Learning Robust Representations with Graph Denoising Policy Network—0
Universal Graph Transformer Self-Attention NetworksCode0
Dimensionwise Separable 2-D Graph Convolution for Unsupervised and Semi-Supervised Learning on GraphsCode0
Towards Interpretable Molecular Graph Representation Learning—0
A bi-diffusion based layer-wise sampling method for deep learning in large graphs—0
Unsupervised Hierarchical Graph Representation Learning with Variational Bayes—0
Empowering Graph Representation Learning with Paired Training and Graph Co-Attention—0
Adaptive Graph Representation Learning for Video Person Re-identificationCode0
Graph Representation Learning: A SurveyCode0
Cross-domain Aspect Category Transfer and Detection via Traceable Heterogeneous Graph Representation LearningCode0
ChainNet: Learning on Blockchain Graphs with Topological Features—0
Symmetric Graph Convolutional Autoencoder for Unsupervised Graph Representation LearningCode0
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Benchmark Results

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