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 501–525 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
Adaptive Fine-Grained Predicates Learning for Scene Graph Generation—0
GEMS: Scene Expansion using Generative Models of Graphs—0
Unsupervised Knowledge Graph Generation Using Semantic Similarity MatchingCode0
Privacy-preserving Graph Analytics: Secure Generation and Federated Learning—0
Learning To Generate Scene Graph from Head to Tail—0
Doubly Reparameterized Importance Weighted Structure Learning for Scene Graph Generation—0
BOND: Benchmarking Unsupervised Outlier Node Detection on Static Attributed GraphsCode0
Robust Attack Graph Generation—0
An Unpooling Layer for Graph GenerationCode0
GraphMapper: Efficient Visual Navigation by Scene Graph Generation—0
Importance Weighted Structure Learning for Scene Graph Generation—0
Learning Reasoning Patterns for Relational Triple Extraction with Mutual Generation of Text and Graph—0
Supplementing Missing Visions via Dialog for Scene Graph GenerationsCode0
Semantic Structure based Query Graph Prediction for Question Answering over Knowledge Graph—0
Synthetic Graph Generation to Benchmark Graph Learning—0
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Benchmark Results

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