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 551–560 of 712 papers

TitleStatusHype
Synthetic Graph Generation to Benchmark Graph Learning—0
Tackling the Unannotated: Scene Graph Generation with Bias-Reduced Models—0
Target-aware Molecular Graph Generation—0
TD^2-Net: Toward Denoising and Debiasing for Dynamic Scene Graph Generation—0
TD-GEN: Graph Generation With Tree Decomposition—0
TextPSG: Panoptic Scene Graph Generation from Textual Descriptions—0
Bayan Algorithm: Detecting Communities in Networks Through Exact and Approximate Optimization of Modularity—0
The Complexity of Symmetry Breaking Beyond Lex-Leader—0
TOMA: Topological Map Abstraction for Reinforcement Learning—0
Topic Scene Graph Generation by Attention Distillation From Caption—0
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Benchmark Results

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