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 231–240 of 712 papers

TitleStatusHype
Generalized Unbiased Scene Graph Generation—0
Generalized Visual Relation Detection with Diffusion Models—0
Generating Triples with Adversarial Networks for Scene Graph Construction—0
Generative AI for Visualization: State of the Art and Future Directions—0
FunGraph: Functionality Aware 3D Scene Graphs for Language-Prompted Scene Interaction—0
Generative Explanations for Graph Neural Network: Methods and Evaluations—0
Generative Graph Convolutional Network for Growing Graphs—0
From Route Instructions to Landmark Graphs—0
Reviving Life on the Edge: Joint Score-Based Graph Generation of Rich Edge Attributes—0
Cyber-Security Knowledge Graph Generation by Hierarchical Nonnegative Matrix Factorization—0
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Benchmark Results

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