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Graph Generation

Graph Generation is an important research area with significant applications in drug and material designs.

Source: Graph Deconvolutional Generation

Papers

Recently Added Most Hyped Most Active Needs Verification Most Verified

Showing 171–180 of 712 papers

Title	Date	Tasks	Status	Hype	Score
Graph Generation with Diffusion Mixture	Feb 7, 2023	3D Molecule GenerationGraph Generation	CodeCode Available	1	5
GraphMaker: Can Diffusion Models Generate Large Attributed Graphs?	Oct 20, 2023	AttributeGraph Generation	CodeCode Available	1	5
GraphGT: Machine Learning Datasets for Graph Generation and Transformation	Sep 24, 2021	BIG-bench Machine LearningDrug Design	CodeCode Available	1	5
GraphGUIDE: interpretable and controllable conditional graph generation with discrete Bernoulli diffusion	Feb 7, 2023	Graph Generation	CodeCode Available	1	5
NODIS: Neural Ordinary Differential Scene Understanding	Jan 14, 2020	AllGraph Generation	CodeCode Available	1	5
Panoptic Video Scene Graph Generation	Nov 28, 2023	Graph GenerationPanoptic Scene Graph Generation	CodeCode Available	1	5
ExplaGraphs: An Explanation Graph Generation Task for Structured Commonsense Reasoning	Apr 15, 2021	Graph GenerationMultiple-choice	CodeCode Available	1	5
Graph Pooling for Graph Neural Networks: Progress, Challenges, and Opportunities	Apr 15, 2022	Graph ClassificationGraph Generation	CodeCode Available	1	5
Adaptive Graph Convolutional Recurrent Network for Traffic Forecasting	Jul 6, 2020	Graph GenerationGraph Neural Network	CodeCode Available	1	5
RLIPv2: Fast Scaling of Relational Language-Image Pre-training	Aug 18, 2023	Graph GenerationHuman-Object Interaction Detection	CodeCode Available	1	5

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Benchmark Results

#	Model	Metric	Claimed	Verified	Status
1	RNN	StreetMover	0.03	—	Unverified
2	GraphRNN	StreetMover	0.02	—	Unverified
3	GGT without CA	StreetMover	0.02	—	Unverified
4	GGT	StreetMover	0.02	—	Unverified