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 641–650 of 712 papers

TitleStatusHype
Let There Be Order: Rethinking Ordering in Autoregressive Graph GenerationCode0
Balanced Graph Structure Learning for Multivariate Time Series ForecastingCode0
Reinforced Molecular Optimization with Neighborhood-Controlled GrammarsCode0
Adaptive Visual Scene Understanding: Incremental Scene Graph GenerationCode0
SteinGen: Generating Fidelitous and Diverse Graph SamplesCode0
KnowZRel: Common Sense Knowledge-based Zero-Shot Relationship Retrieval for Generalised Scene Graph GenerationCode0
Interpretable Deep Graph Generation with Node-Edge Co-DisentanglementCode0
Unsupervised Knowledge Graph Generation Using Semantic Similarity MatchingCode0
A Deep Probabilistic Framework for Continuous Time Dynamic Graph GenerationCode0
Instruction-Based Molecular Graph Generation with Unified Text-Graph Diffusion ModelCode0
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Benchmark Results

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