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 471–480 of 712 papers

TitleStatusHype
Influence Maximization (IM) in Complex Networks with Limited Visibility Using Statistical Methods—0
Informative Scene Graph Generation via Debiasing—0
In-game Residential Home Planning via Visual Context-aware Global Relation Learning—0
Instance-incremental Scene Graph Generation from Real-world Point Clouds via Normalizing Flows—0
Instant Policy: In-Context Imitation Learning via Graph Diffusion—0
Interpretable End-to-End Driving Model for Implicit Scene Understanding—0
Interpretable Molecular Graph Generation via Monotonic Constraints—0
Interpreting Equivariant Representations—0
Is 3-(F)WL Enough to Distinguish All 3D Graphs?—0
IS-GGT: Iterative Scene Graph Generation With Generative Transformers—0
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Benchmark Results

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