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 521–530 of 712 papers

TitleStatusHype
Zero-Shot Scene Graph Relation Prediction through Commonsense Knowledge IntegrationCode1
Predicate correlation learning for scene graph generation—0
Evaluating the Cybersecurity Risk of Real World, Machine Learning Production Systems—0
On-Demand and Lightweight Knowledge Graph Generation -- a Demonstration with DBpediaCode0
Non-isomorphic Inter-modality Graph Alignment and Synthesis for Holistic Brain MappingCode0
Molecule Generation by Principal Subgraph Mining and AssemblingCode1
HDMapGen: A Hierarchical Graph Generative Model of High Definition Maps—0
Structured Sparse R-CNN for Direct Scene Graph GenerationCode1
TD-GEN: Graph Generation With Tree Decomposition—0
Graph Context Encoder: Graph Feature Inpainting for Graph Generation and Self-supervised Pretraining—0
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Benchmark Results

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