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 461–470 of 712 papers

TitleStatusHype
Interpretable Molecular Graph Generation via Monotonic Constraints—0
Commonsense Reasoning for Identifying and Understanding the Implicit Need of Help and Synthesizing Assistive Actions—0
One-shot Scene Graph GenerationCode1
Relation Regularized Scene Graph Generation—0
OG-SGG: Ontology-Guided Scene Graph Generation. A Case Study in Transfer Learning for Telepresence RoboticsCode0
Fairness Amidst Non-IID Graph Data: A Literature Review—0
Hyper-relationship Learning Network for Scene Graph Generation—0
Target-aware Molecular Graph Generation—0
Score-based Generative Modeling of Graphs via the System of Stochastic Differential EquationsCode1
FastFlows: Flow-Based Models for Molecular Graph GenerationCode2
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Benchmark Results

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