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 321–330 of 712 papers

TitleStatusHype
Enhanced Data Transfer Cooperating with Artificial Triplets for Scene Graph Generation—0
CAT-SG: A Large Dynamic Scene Graph Dataset for Fine-Grained Understanding of Cataract Surgery—0
Adversarial Stein Training for Graph Energy Models—0
Adversarial Stein Training for Graph Energy Models—0
Is 3-(F)WL Enough to Distinguish All 3D Graphs?—0
iTelos -- Purpose Driven Knowledge Graph Generation—0
ICST-DNET: An Interpretable Causal Spatio-Temporal Diffusion Network for Traffic Speed Prediction—0
Hyper-relationship Learning Network for Scene Graph Generation—0
HyperGLM: HyperGraph for Video Scene Graph Generation and Anticipation—0
Context-aware Mixture-of-Experts for Unbiased 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