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 661–670 of 712 papers

TitleStatusHype
Continuous Graph Flow—0
Understanding the Representation Power of Graph Neural Networks in Learning Graph TopologyCode0
The Limited Multi-Label Projection LayerCode0
Learning Predicates as Functions to Enable Few-shot Scene Graph Prediction—0
Deep Q-Learning for Directed Acyclic Graph Generation—0
Scalable Generative Models for Graphs with Graph Attention Mechanism—0
Exploring Context and Visual Pattern of Relationship for Scene Graph Generation—0
Contextual Translation Embedding for Visual Relationship Detection and Scene Graph Generation—0
GraphNVP: An Invertible Flow Model for Generating Molecular GraphsCode0
Target-Tailored Source-Transformation for Scene Graph Generation—0
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Benchmark Results

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