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 211–220 of 712 papers

TitleStatusHype
Pixel-wise Graph Attention Networks for Person Re-identificationCode0
Optimized Crystallographic Graph Generation for Material ScienceCode0
AgraSSt: Approximate Graph Stein Statistics for Interpretable Assessment of Implicit Graph GeneratorsCode0
OG-SGG: Ontology-Guided Scene Graph Generation. A Case Study in Transfer Learning for Telepresence RoboticsCode0
Adaptive Visual Scene Understanding: Incremental Scene Graph GenerationCode0
Non-isomorphic Inter-modality Graph Alignment and Synthesis for Holistic Brain MappingCode0
On-Demand and Lightweight Knowledge Graph Generation -- a Demonstration with DBpediaCode0
Pre-Training on Dynamic Graph Neural NetworksCode0
NetGAN: Generating Graphs via Random WalksCode0
Narrative-of-Thought: Improving Temporal Reasoning of Large Language Models via Recounted NarrativesCode0
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Benchmark Results

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