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Graph Generation

Graph Generation is an important research area with significant applications in drug and material designs.

Source: Graph Deconvolutional Generation

Papers

Recently Added Most Hyped Most Active Needs Verification Most Verified

Showing 691–700 of 712 papers

Title	Date	Tasks	Status	Hype
Aesthetic Discrimination of Graph Layouts	Sep 4, 2018	Data AugmentationGraph Generation	CodeCode Available	0
Sequence-to-Action: End-to-End Semantic Graph Generation for Semantic Parsing	Sep 4, 2018	Graph GenerationRepresentation Learning	CodeCode Available	0
Natural Language Processing for Music Knowledge Discovery	Jul 6, 2018	Graph GenerationSentiment Analysis	CodeCode Available	0
Factorizable Net: An Efficient Subgraph-based Framework for Scene Graph Generation	Jun 29, 2018	ClusteringGraph Generation	CodeCode Available	0
Graph Convolutional Policy Network for Goal-Directed Molecular Graph Generation	Jun 7, 2018	Graph GenerationMolecular Graph Generation	CodeCode Available	0
A posteriori multi-stage optimal trading under transaction costs and a diversification constraint	Apr 25, 2018	Graph GenerationTime Series	—Unverified	0
Approximate Query Matching for Image Retrieval	Mar 14, 2018	Graph GenerationImage Retrieval	—Unverified	0
Learning Deep Generative Models of Graphs	Mar 8, 2018	Graph GenerationKnowledge Graphs	—Unverified	0
NetGAN: Generating Graphs via Random Walks	Mar 2, 2018	Graph GenerationLink Prediction	CodeCode Available	0
Growing Story Forest Online from Massive Breaking News	Mar 1, 2018	Graph GenerationInformation Threading	CodeCode Available	0

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Benchmark Results

#	Model	Metric	Claimed	Verified	Status
1	RNN	StreetMover	0.03	—	Unverified
2	GraphRNN	StreetMover	0.02	—	Unverified
3	GGT without CA	StreetMover	0.02	—	Unverified
4	GGT	StreetMover	0.02	—	Unverified