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 591–600 of 712 papers

TitleStatusHype
SHADOWCAST: Controllable Graph Generation with Explainability—0
Are scene graphs good enough to improve Image Captioning?Code1
Topology-Aware Generative Adversarial Network for Joint Prediction of Multiple Brain Graphs from a Single Brain GraphCode1
Adversarial Stein Training for Graph Energy Models—0
CogTree: Cognition Tree Loss for Unbiased Scene Graph GenerationCode1
Exploring the Hierarchy in Relation Labels for Scene Graph Generation—0
PCPL: Predicate-Correlation Perception Learning for Unbiased Scene Graph GenerationCode1
Tackling the Unannotated: Scene Graph Generation with Bias-Reduced Models—0
Graph Polish: A Novel Graph Generation Paradigm for Molecular Optimization—0
HOSE-Net: Higher Order Structure Embedded Network for Scene Graph Generation—0
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Benchmark Results

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