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 501–550 of 712 papers

TitleStatusHype
Exploring Edge Probability Graph Models Beyond Edge Independency: Concepts, Analyses, and Algorithms—0
Exploring Graph Classification Techniques Under Low Data Constraints: A Comprehensive Study—0
Exploring the Hierarchy in Relation Labels for Scene Graph Generation—0
Exploring the Potential of Large Language Models in Graph Generation—0
Target-Tailored Source-Transformation for Scene Graph Generation—0
FactReranker: Fact-guided Reranker for Faithful Radiology Report Summarization—0
FairGen: Towards Fair Graph Generation—0
Fairness Amidst Non-IID Graph Data: A Literature Review—0
FairWire: Fair Graph Generation—0
Fast Contextual Scene Graph Generation With Unbiased Context Augmentation—0
Finding Increasingly Large Extremal Graphs with AlphaZero and Tabu Search—0
Flatten Graphs as Sequences: Transformers are Scalable Graph Generators—0
FLOWGEN: Fast and slow graph generation—0
Focused Discriminative Training For Streaming CTC-Trained Automatic Speech Recognition Models—0
Form follows Function: Text-to-Text Conditional Graph Generation based on Functional Requirements—0
FragFM: Hierarchical Framework for Efficient Molecule Generation via Fragment-Level Discrete Flow Matching—0
FreeQ-Graph: Free-form Querying with Semantic Consistent Scene Graph for 3D Scene Understanding—0
From Data to Modeling: Fully Open-vocabulary Scene Graph Generation—0
From Easy to Hard: Learning Curricular Shape-aware Features for Robust Panoptic Scene Graph Generation—0
From Graph Generation to Graph Classification—0
From Route Instructions to Landmark Graphs—0
FunGraph: Functionality Aware 3D Scene Graphs for Language-Prompted Scene Interaction—0
G2A2: An Automated Graph Generator with Attributes and Anomalies—0
GEMS: Scene Expansion using Generative Models of Graphs—0
Generalized Unbiased Scene Graph Generation—0
Generalized Visual Relation Detection with Diffusion Models—0
Generating Triples with Adversarial Networks for Scene Graph Construction—0
Generative AI for Visualization: State of the Art and Future Directions—0
Generative Explanations for Graph Neural Network: Methods and Evaluations—0
Generative Graph Convolutional Network for Growing Graphs—0
Reviving Life on the Edge: Joint Score-Based Graph Generation of Rich Edge Attributes—0
Generative modeling of the enteric nervous system employing point pattern analysis and graph construction—0
GeSubNet: Gene Interaction Inference for Disease Subtype Network Generation—0
GG-GAN: A Geometric Graph Generative Adversarial Network—0
Scalable Generative Models for Graphs with Graph Attention Mechanism—0
Gransformer: Transformer-based Graph Generation—0
Graph Autoencoders with Deconvolutional Networks—0
Graph-Aware Transformer: Is Attention All Graphs Need?—0
Graph Community Augmentation with GMM-based Modeling in Latent Space—0
Graph Context Encoder: Graph Feature Inpainting for Graph Generation and Self-supervised Pretraining—0
Graph Deconvolutional Generation—0
GraphDF: A Discrete Flow Model for Molecular Graph Generation—0
GraphEBM: Towards Permutation Invariant and Multi-Objective Molecular Graph Generation—0
Graph Embedding VAE: A Permutation Invariant Model of Graph Structure—0
Graph Energy-based Model for Molecular Graph Generation—0
GraphGAN: Generating Graphs via Random Walks—0
Graph Generation via Scattering—0
Graph Generation via Spectral Diffusion—0
Graph Generation with Variational Recurrent Neural Network—0
Graph Generative Pre-trained Transformer—0
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Benchmark Results

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