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 381–390 of 712 papers

TitleStatusHype
Swap-based Deep Reinforcement Learning for Facility Location Problems in Networks—0
Indoor and Outdoor 3D Scene Graph Generation via Language-Enabled Spatial Ontologies—0
Collect and Connect Data Leaves to Feature Concepts: Interactive Graph Generation Toward Well-being—0
GPT4SGG: Synthesizing Scene Graphs from Holistic and Region-specific NarrativesCode0
HIG: Hierarchical Interlacement Graph Approach to Scene Graph Generation in Video Understanding—0
HAtt-Flow: Hierarchical Attention-Flow Mechanism for Group Activity Scene Graph Generation in Videos—0
RetroDiff: Retrosynthesis as Multi-stage Distribution Interpolation—0
Exploring Graph Classification Techniques Under Low Data Constraints: A Comprehensive Study—0
Two Stream Scene Understanding on Graph Embedding—0
Identification of vortex in unstructured mesh with graph neural networks—0
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Benchmark Results

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