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 651–660 of 712 papers

TitleStatusHype
From Route Instructions to Landmark Graphs—0
Unbiased Scene Graph Generation via Rich and Fair Semantic Extraction—0
Edge-based sequential graph generation with recurrent neural networksCode0
Graph Generators: State of the Art and Open Challenges—0
Deep imitation learning for molecular inverse problems—0
Effective Decoding in Graph Auto-Encoder using Triadic Closure—0
Multi-MotifGAN (MMGAN): Motif-targeted Graph Generation and Prediction—0
Image-Conditioned Graph Generation for Road Network ExtractionCode0
Leveraging Auxiliary Text for Deep Recognition of Unseen Visual Relationships—0
Graph Embedding VAE: A Permutation Invariant Model of Graph Structure—0
Show:102550
← PrevPage 66 of 72Next →

Benchmark Results

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