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 601–610 of 712 papers

TitleStatusHype
Topic Scene Graph Generation by Attention Distillation From Caption—0
GG-GAN: A Geometric Graph Generative Adversarial Network—0
A Simple Baseline for Weakly-Supervised Scene Graph Generation—0
Graph Edit NetworksCode0
Learning Latent Topology for Graph Matching—0
Deep Graph Generators: A Survey—0
MG-SAGC: A multiscale graph and its self-adaptive graph convolution network for 3D point clouds—0
Graph Autoencoders with Deconvolutional Networks—0
Molecular graph generation with Graph Neural Networks—0
A graph similarity for deep learning—0
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Benchmark Results

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