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
Assisting Scene Graph Generation with Self-Supervision—0
Structural Plan of Indoor Scenes with Personalized Preferences—0
Mix Dimension in Poincaré Geometry for 3D Skeleton-based Action Recognition—0
Sketching Image Gist: Human-Mimetic Hierarchical Scene Graph GenerationCode1
A Systematic Survey on Deep Generative Models for Graph Generation—0
Generative Compositional Augmentations for Scene Graph PredictionCode1
Learning and Reasoning with the Graph Structure Representation in Robotic SurgeryCode1
Adaptive Graph Convolutional Recurrent Network for Traffic ForecastingCode1
Query Graph Generation for Answering Multi-hop Complex Questions from Knowledge Bases—0
Scalable Deep Generative Modeling for Sparse Graphs—0
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Benchmark Results

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