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 701–712 of 712 papers

TitleStatusHype
Generating Triples with Adversarial Networks for Scene Graph Construction—0
A Novel Weighted Distance Measure for Multi-Attributed Graph—0
GraphGAN: Generating Graphs via Random Walks—0
Dynamic Graph Generation Network: Generating Relational Knowledge from Diagrams—0
Python Random Graph Generator—0
Scene Graph Generation from Objects, Phrases and Region CaptionsCode0
Pixels to Graphs by Associative EmbeddingCode0
Scene Graph Generation by Iterative Message PassingCode1
Node Embedding via Word Embedding for Network Community DiscoveryCode0
Semantic Parsing via Staged Query Graph Generation: Question Answering with Knowledge BaseCode0
Effects of Graph Generation for Unsupervised Non-Contextual Single Document Keyword Extraction—0
Pre-processing of Domain Ontology Graph Generation System in Punjabi—0
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Benchmark Results

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