SOTAVerified

Graph Generation

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

Source: Graph Deconvolutional Generation

Papers

Recently AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 671–680 of 712 papers

TitleStatusHype
Scalable Generative Models for Graphs with Graph Attention Mechanism—0
Deep Q-Learning for Directed Acyclic Graph Generation—0
Exploring Context and Visual Pattern of Relationship for Scene Graph Generation—0
GraphNVP: An Invertible Flow Model for Generating Molecular GraphsCode0
Contextual Translation Embedding for Visual Relationship Detection and Scene Graph Generation—0
Target-Tailored Source-Transformation for Scene Graph Generation—0
Scene Graph Generation with External Knowledge and Image Reconstruction—0
An End-to-End Network for Generating Social Relationship Graphs—0
Visual Semantic Information Pursuit: A Survey—0
Generative Graph Convolutional Network for Growing Graphs—0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1RNNStreetMover0.03—Unverified
2GraphRNNStreetMover0.02—Unverified
3GGT without CAStreetMover0.02—Unverified
4GGTStreetMover0.02—Unverified