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 531–540 of 712 papers

TitleStatusHype
Disentangled Spatiotemporal Graph Generative Models—0
Interpretable Molecular Graph Generation via Monotonic Constraints—0
Commonsense Reasoning for Identifying and Understanding the Implicit Need of Help and Synthesizing Assistive Actions—0
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
GraphTune: A Learning-based Graph Generative Model with Tunable Structural FeaturesCode0
Constrained Structure Learning 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