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 311–320 of 712 papers

TitleStatusHype
Using Motif Transitions for Temporal Graph GenerationCode0
Multi-Label Meta Weighting for Long-Tailed Dynamic Scene Graph GenerationCode0
On Certified Generalization in Structured Prediction—0
Hyperbolic Graph Diffusion ModelCode1
Discrete Graph Auto-Encoder—0
Single-Stage Visual Relationship Learning using Conditional Queries—0
Optimized Crystallographic Graph Generation for Material ScienceCode0
LIC-GAN: Language Information Conditioned Graph Generative GAN Model—0
Explanation Graph Generation via Generative Pre-training over Synthetic GraphsCode0
HiGen: Hierarchical Graph Generative NetworksCode1
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Benchmark Results

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