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 401–450 of 712 papers

TitleStatusHype
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
Graph Generators: State of the Art and Open Challenges—0
Graph Guided Diffusion: Unified Guidance for Conditional Graph Generation—0
GraphMapper: Efficient Visual Navigation by Scene Graph Generation—0
GraphMimic: Graph-to-Graphs Generative Modeling from Videos for Policy Learning—0
GraphNVP: an Invertible Flow-based Model for Generating Molecular Graphs—0
Graph Polish: A Novel Graph Generation Paradigm for Molecular Optimization—0
GraphRCG: Self-Conditioned Graph Generation—0
Graph Residual Flow for Molecular Graph Generation—0
Graphs over Time: Densification Laws, Shrinking Diameters and Possible Explanations—0
Graphs Unveiled: Graph Neural Networks and Graph Generation—0
GUISE: Graph GaUssIan Shading watErmark—0
HAtt-Flow: Hierarchical Attention-Flow Mechanism for Group Activity Scene Graph Generation in Videos—0
HDMapGen: A Hierarchical Graph Generative Model of High Definition Maps—0
Heterogeneous Graph Generation: A Hierarchical Approach using Node Feature Pooling—0
Hi-Dyna Graph: Hierarchical Dynamic Scene Graph for Robotic Autonomy in Human-Centric Environments—0
Size Matters: Large Graph Generation with HiGGs—0
Hierarchical Memory Learning for Fine-Grained Scene Graph Generation—0
On Hierarchical Multi-Resolution Graph Generative Models—0
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Benchmark Results

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