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 611–620 of 712 papers

TitleStatusHype
Latency Optimization in LEO Satellite Communications with Hybrid Beam Pattern and Interference Control—0
Learning 4D Panoptic Scene Graph Generation from Rich 2D Visual Scene—0
Learning Deep Generative Models of Graphs—0
Learning from the Scene and Borrowing from the Rich: Tackling the Long Tail in Scene Graph Generation—0
Learning Latent Topology for Graph Matching—0
Learning of Visual Relations: The Devil is in the Tails—0
Learning-Order Autoregressive Models with Application to Molecular Graph Generation—0
Learning Reasoning Patterns for Relational Triple Extraction with Mutual Generation of Text and Graph—0
Learning To Generate Scene Graph from Head to Tail—0
Learning to Generate Time Series Conditioned Graphs with Generative Adversarial Nets—0
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Benchmark Results

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