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 211–220 of 712 papers

TitleStatusHype
CoPa-SG: Dense Scene Graphs with Parametric and Proto-Relations—0
CAT-SG: A Large Dynamic Scene Graph Dataset for Fine-Grained Understanding of Cataract Surgery—0
HOIverse: A Synthetic Scene Graph Dataset With Human Object Interactions—0
FreeQ-Graph: Free-form Querying with Semantic Consistent Scene Graph for 3D Scene Understanding—0
Bures-Wasserstein Flow Matching for Graph Generation—0
Representing Time-Continuous Behavior of Cyber-Physical Systems in Knowledge Graphs—0
Out-of-Distribution Graph Models Merging—0
Hi-Dyna Graph: Hierarchical Dynamic Scene Graph for Robotic Autonomy in Human-Centric Environments—0
Studying and Improving Graph Neural Network-based Motif Estimation—0
A Reverse Causal Framework to Mitigate Spurious Correlations for Debiasing 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