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 421–430 of 712 papers

TitleStatusHype
Graph Community Augmentation with GMM-based Modeling in Latent Space—0
Graph Context Encoder: Graph Feature Inpainting for Graph Generation and Self-supervised Pretraining—0
Graph Deconvolutional Generation—0
GraphDF: A Discrete Flow Model for Molecular Graph Generation—0
GraphEBM: Towards Permutation Invariant and Multi-Objective Molecular Graph Generation—0
Graph Embedding VAE: A Permutation Invariant Model of Graph Structure—0
Graph Energy-based Model for Molecular Graph Generation—0
GraphGAN: Generating Graphs via Random Walks—0
Graph Generation via Scattering—0
Graph Generation via Spectral Diffusion—0
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Benchmark Results

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