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 501–510 of 712 papers

TitleStatusHype
Influence Maximization (IM) in Complex Networks with Limited Visibility Using Statistical Methods—0
Towards Open-vocabulary Scene Graph Generation with Prompt-based Finetuning—0
Context-aware Mixture-of-Experts for Unbiased Scene Graph Generation—0
Label Semantic Knowledge Distillation for Unbiased Scene Graph Generation—0
Rethinking the Evaluation of Unbiased Scene Graph Generation—0
Iterative Scene Graph Generation—0
NICEST: Noisy Label Correction and Training for Robust Scene Graph Generation—0
An Urban Population Health Observatory for Disease Causal Pathway Analysis and Decision Support: Underlying Explainable Artificial Intelligence Model—0
Meta Spatio-Temporal Debiasing for Video Scene Graph Generation—0
FLOWGEN: Fast and slow graph generation—0
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Benchmark Results

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