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Graph Embedding

Graph embeddings learn a mapping from a network to a vector space, while preserving relevant network properties.

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Papers

Recently Added Most Hyped Most Active Needs Verification Most Verified

Showing 971–980 of 1192 papers

Title	Date	Tasks	Status	Hype
A Relational Memory-based Embedding Model for Triple Classification and Search Personalization	Jul 13, 2019	DecoderGeneral Classification	CodeCode Available	0
Mercem: Method Name Recommendation Based on Call Graph Embedding	Jul 12, 2019	Graph Embedding	—Unverified	0
Semi-Supervised Graph Embedding for Multi-Label Graph Node Classification	Jul 12, 2019	ClassificationGeneral Classification	—Unverified	0
GraphSAINT: Graph Sampling Based Inductive Learning Method	Jul 10, 2019	Graph AttentionGraph Embedding	CodeCode Available	1
Graph Representation Learning via Hard and Channel-Wise Attention Networks	Jul 5, 2019	Graph AttentionGraph Classification	CodeCode Available	0
Network Embedding: on Compression and Learning	Jul 5, 2019	Graph EmbeddingMulti-Label Classification	CodeCode Available	0
Graph Embeddings at Scale	Jul 3, 2019	Graph Embeddinggraph partitioning	—Unverified	0
Knowledge Graph Embedding for Ecotoxicological Effect Prediction	Jul 2, 2019	Graph EmbeddingKnowledge Graph Embedding	CodeCode Available	0
From Node Embedding To Community Embedding : A Hyperbolic Approach	Jul 2, 2019	Community DetectionGraph Embedding	CodeCode Available	0
Zero-shot Word Sense Disambiguation using Sense Definition Embeddings	Jul 1, 2019	Generalized Zero-Shot LearningGraph Embedding	CodeCode Available	0

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Benchmark Results

#	Model	Metric	Claimed	Verified	Status
1	DeepGG	Entropy Difference	0	—	Unverified