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 401–425 of 982 papers

TitleStatusHype
Contrastive Brain Network Learning via Hierarchical Signed Graph Pooling Model—0
Deep Learning on Graphs for Natural Language Processing—0
GCN-BMP: Investigating Graph Representation Learning for DDI Prediction Task—0
X-GOAL: Multiplex Heterogeneous Graph Prototypical Contrastive Learning—0
Deep Multi-attribute Graph Representation Learning on Protein Structures—0
Graph Neural Networks for Binary Programming—0
A Survey on Heterogeneous Graph Embedding: Methods, Techniques, Applications and Sources—0
G5: A Universal GRAPH-BERT for Graph-to-Graph Transfer and Apocalypse Learning—0
Graph Neural Networks Provably Benefit from Structural Information: A Feature Learning Perspective—0
Consensus Graph Representation Learning for Better Grounded Image Captioning—0
From random-walks to graph-sprints: a low-latency node embedding framework on continuous-time dynamic graphs—0
A Survey on Graph Representation Learning Methods—0
Graph Ordering: Towards the Optimal by Learning—0
Graph Partial Label Learning with Potential Cause Discovering—0
Graph Persistence goes Spectral—0
GraphPMU: Event Clustering via Graph Representation Learning Using Locationally-Scarce Distribution-Level Fundamental and Harmonic PMU Measurements—0
Delayed Bottlenecking: Alleviating Forgetting in Pre-trained Graph Neural Networks—0
3D Hand Pose Estimation via Regularized Graph Representation Learning—0
Harvesting Textual and Structured Data from the HAL Publication Repository—0
Haste Makes Waste: A Simple Approach for Scaling Graph Neural Networks—0
Detection of Fake Users in SMPs Using NLP and Graph Embeddings—0
A Deep Latent Space Model for Directed Graph Representation Learning—0
A Survey on Graph Neural Networks and Graph Transformers in Computer Vision: A Task-Oriented Perspective—0
Graph Representation learning for Audio & Music genre Classification—0
FMGNN: Fused Manifold Graph Neural Network—0
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Benchmark Results

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