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 91–100 of 712 papers

TitleStatusHype
Contrastive Graph Condensation: Advancing Data Versatility through Self-Supervised Learning—0
TreeFormer: Single-view Plant Skeleton Estimation via Tree-constrained Graph GenerationCode0
Towards Unbiased and Robust Spatio-Temporal Scene Graph Generation and Anticipation—0
Unbiased Scene Graph Generation by Type-Aware Message Passing on Heterogeneous and Dual Graphs—0
Instant Policy: In-Context Imitation Learning via Graph Diffusion—0
Latency Optimization in LEO Satellite Communications with Hybrid Beam Pattern and Interference Control—0
Improving Molecular Graph Generation with Flow Matching and Optimal Transport—0
LayerDAG: A Layerwise Autoregressive Diffusion Model for Directed Acyclic Graph GenerationCode1
Federated Voxel Scene Graph for Intracranial HemorrhageCode0
Diffusion Twigs with Loop Guidance for Conditional Graph GenerationCode0
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Benchmark Results

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