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 421–430 of 712 papers

TitleStatusHype
Assisting Scene Graph Generation with Self-Supervision—0
A Survey on Deep Graph Generation: Methods and Applications—0
A Systematic Survey on Deep Generative Models for Graph Generation—0
Attentive Relational Networks for Mapping Images to Scene Graphs—0
A Tunable Model for Graph Generation Using LSTM and Conditional VAE—0
AUG: A New Dataset and An Efficient Model for Aerial Image Urban Scene Graph Generation—0
Automated Generation of Precedence Graphs in Digital Value Chains for Automotive Production—0
Automated Graph Generation at Sentence Level for Reading Comprehension Based on Conceptual Graphs—0
Backdoor Attacks on Discrete Graph Diffusion Models—0
BCTR: Bidirectional Conditioning Transformer for Scene Graph Generation—0
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Benchmark Results

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