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 411–420 of 712 papers

TitleStatusHype
Scalable Regularization of Scene Graph Generation Models using Symbolic Theories—0
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
Integrating Object-aware and Interaction-aware Knowledge for Weakly Supervised Scene Graph GenerationCode1
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
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Benchmark Results

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