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 671–680 of 712 papers

TitleStatusHype
Point2Graph: An End-to-end Point Cloud-based 3D Open-Vocabulary Scene Graph for Robot Navigation—0
PPDL: Predicate Probability Distribution Based Loss for Unbiased Scene Graph Generation—0
Predicate Classification Using Optimal Transport Loss in Scene Graph Generation—0
Predicate correlation learning for scene graph generation—0
Pre-processing of Domain Ontology Graph Generation System in Punjabi—0
Pretraining Generative Flow Networks with Inexpensive Rewards for Molecular Graph Generation—0
Privacy-preserving Graph Analytics: Secure Generation and Federated Learning—0
Private Synthetic Graph Generation and Fused Gromov-Wasserstein Distance—0
Python Random Graph Generator—0
Query Graph Generation for Answering Multi-hop Complex Questions from Knowledge Bases—0
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Benchmark Results

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