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 401–410 of 712 papers

TitleStatusHype
Evaluating the Cybersecurity Risk of Real World, Machine Learning Production Systems—0
A Framework for Large Scale Synthetic Graph Dataset Generation—0
A graph similarity for deep learning—0
A Hard Label Black-box Adversarial Attack Against Graph Neural Networks—0
A Modern Take on Visual Relationship Reasoning for Grasp Planning—0
An Accurate Graph Generative Model with Tunable Features—0
AnalogXpert: Automating Analog Topology Synthesis by Incorporating Circuit Design Expertise into Large Language Models—0
Analyzing Hong Kong's Legal Judgments from a Computational Linguistics point-of-view—0
An Automated Domain Understanding Technique for Knowledge Graph Generation—0
An End-to-End Network for Generating Social Relationship Graphs—0
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Benchmark Results

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