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
Adaptive Fine-Grained Predicates Learning for Scene Graph Generation—0
GEMS: Scene Expansion using Generative Models of Graphs—0
Unsupervised Knowledge Graph Generation Using Semantic Similarity MatchingCode0
Privacy-preserving Graph Analytics: Secure Generation and Federated Learning—0
Learning To Generate Scene Graph from Head to Tail—0
Doubly Reparameterized Importance Weighted Structure Learning for Scene Graph Generation—0
BOND: Benchmarking Unsupervised Outlier Node Detection on Static Attributed GraphsCode0
Robust Attack Graph Generation—0
An Unpooling Layer for Graph GenerationCode0
GraphMapper: Efficient Visual Navigation by 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