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 631–640 of 712 papers

TitleStatusHype
Structural Plan of Indoor Scenes with Personalized Preferences—0
Mix Dimension in Poincaré Geometry for 3D Skeleton-based Action Recognition—0
A Systematic Survey on Deep Generative Models for Graph Generation—0
Query Graph Generation for Answering Multi-hop Complex Questions from Knowledge Bases—0
Scalable Deep Generative Modeling for Sparse Graphs—0
Neuro-Symbolic Visual Reasoning: Disentangling "Visual" from "Reasoning"—0
MALOnt: An Ontology for Malware Threat IntelligenceCode0
Learning from the Scene and Borrowing from the Rich: Tackling the Long Tail in Scene Graph Generation—0
Heuristic Semi-Supervised Learning for Graph Generation Inspired by Electoral CollegeCode0
Interpretable Deep Graph Generation with Node-Edge Co-DisentanglementCode0
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Benchmark Results

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