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 111–120 of 712 papers

TitleStatusHype
GraphGUIDE: interpretable and controllable conditional graph generation with discrete Bernoulli diffusionCode1
CycleGT: Unsupervised Graph-to-Text and Text-to-Graph Generation via Cycle TrainingCode1
GPS-Net: Graph Property Sensing Network for Scene Graph GenerationCode1
Data Imputation with Iterative Graph ReconstructionCode1
Face Super-Resolution Using Stochastic Differential EquationsCode1
GPT-GNN: Generative Pre-Training of Graph Neural NetworksCode1
DIFFVSGG: Diffusion-Driven Online Video Scene Graph GenerationCode1
GraphAF: a Flow-based Autoregressive Model for Molecular Graph GenerationCode1
Graph Diffusion Policy OptimizationCode1
GraphGT: Machine Learning Datasets for Graph Generation and TransformationCode1
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Benchmark Results

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