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 511–520 of 712 papers

TitleStatusHype
A Hard Label Black-box Adversarial Attack Against Graph Neural Networks—0
Semantic Compositional Learning for Low-shot Scene Graph Generation—0
Computing Steiner Trees using Graph Neural Networks—0
Target Adaptive Context Aggregation for Video Scene Graph GenerationCode1
Unconditional Scene Graph Generation—0
ReFormer: The Relational Transformer for Image CaptioningCode0
Image Scene Graph Generation (SGG) Benchmark—0
WikiGraphs: A Wikipedia Text - Knowledge Graph Paired DatasetCode0
GraphGen-Redux: a Fast and Lightweight Recurrent Model for labeled Graph GenerationCode0
Scenes and Surroundings: Scene Graph Generation using Relation TransformerCode1
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Benchmark Results

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