mlsanityData to 7 Oct 2026

A Survey on Graph Diffusion Models: Generative AI in Science for Molecule, Protein and Material

arXiv 2304.01565 ↗First posted 4 Apr 2023cs.LG cs.CVcited by 34

On the map: Diffusion models → Flow matching, time series and science

Abstract (arXiv)

Diffusion models have become a new SOTA generative modeling method in various fields, for which there are multiple survey works that provide an overall survey. With the number of articles on diffusion models increasing exponentially in the past few years, there is an increasing need for surveys of diffusion models on specific fields. In this work, we are committed to conducting a survey on the graph diffusion models. Even though our focus is to cover the progress of diffusion models in graphs, we first briefly summarize how other generative modeling methods are used for graphs. After that, we introduce the mechanism of diffusion models in various forms, which facilitates the discussion on the graph diffusion models. The applications of graph diffusion models mainly fall into the category of AI-generated content (AIGC) in science, for which we mainly focus on how graph diffusion models are utilized for generating molecules and proteins but also cover other cases, including materials design. Moreover, we discuss the issue of evaluating diffusion models in the graph domain and the existing challenges.

Key facts. Cited by 34 papers in the map (data through 7 Oct 2026). Placed in Flow matching, time series and science, one of 14 directions in Diffusion models. Builds on 105 of its 149 references that are in the map. First posted on arXiv 4 Apr 2023.

Builds on

105 of 149 references.

Closest ancestors · 12

Same direction, newest first

  1. 2022NVDiff: Graph Generation through the Diffusion of Node Vectors19 Nov
  2. 2022Structure-based Drug Design with Equivariant Diffusion Models24 Oct
  3. 2022Equivariant 3D-Conditional Diffusion Models for Molecular Linker Design11 Oct
  4. 2022Protein structure generation via folding diffusion30 Sep
  5. 2022DiGress: Discrete Denoising diffusion for graph generation29 Sep
  6. 2022MDM: Molecular Diffusion Model for 3D Molecule Generation13 Sep
  7. 2022Diffusion probabilistic modeling of protein backbones in 3D for the motif-scaffolding problem8 Jun
  8. 2022Protein Structure and Sequence Generation with Equivariant Denoising Diffusion Probabilistic Models26 May
  9. 2022Equivariant Diffusion for Molecule Generation in 3D31 Mar
  10. 2022GeoDiff: a Geometric Diffusion Model for Molecular Conformation Generation6 Mar
  11. 2022Score-based Generative Modeling of Graphs via the System of Stochastic Differential Equations5 Feb
  12. 2020Permutation Invariant Graph Generation via Score-Based Generative Modeling2 Mar

Other references · 93

  1. 2017Attention Is All You Needcited by 59,932
  2. 2020Denoising Diffusion Probabilistic Modelscited by 20,851
  3. 2016Semi-Supervised Classification with Graph Convolutional Networkscited by 11,282
  4. 2020Score-Based Generative Modeling through Stochastic Differential Equationscited by 8,964
  5. 2017Graph Attention Networkscited by 8,854
  6. 2021Diffusion Models Beat GANs on Image Synthesiscited by 8,185
  7. 2017Inductive Representation Learning on Large Graphscited by 6,284
  8. 2022Generative Adversarial Networkscited by 5,603
  9. 2018How Powerful are Graph Neural Networks?cited by 4,355
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  11. 2019Generative Modeling by Estimating Gradients of the Data Distributioncited by 4,067
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38 more
  1. 2017Neural Message Passing for Quantum Chemistrycited by 3,460
  2. 2014Sequence to Sequence Learning with Neural Networkscited by 2,974
  3. 2016Improved Techniques for Training GANscited by 2,938
  4. 2015Variational Inference with Normalizing Flowscited by 2,161
  5. 2014Conditional Generative Adversarial Netscited by 2,152
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  7. 2016Density estimation using Real NVPcited by 2,029
  8. 2018Graph Neural Networks: A Review of Methods and Applicationscited by 1,571
  9. 2014DeepWalk: Online Learning of Social Representationscited by 1,543
  10. 2016Variational Graph Auto-Encoderscited by 1,373
  11. 2018Graph Convolutional Neural Networks for Web-Scale Recommender Systemscited by 1,133
  12. 2022Diffusion Models: A Comprehensive Survey of Methods and Applicationscited by 1,107
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  15. 2017MoleculeNet: A Benchmark for Molecular Machine Learningcited by 1,037
  16. 2020Improved Techniques for Training Score-Based Generative Modelscited by 1,036
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  18. 2021E(n) Equivariant Graph Neural Networkscited by 951
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  20. 2016Automatic chemical design using a data-driven continuous representation of moleculescited by 762
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  22. 2019Heterogeneous Graph Attention Networkcited by 732
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  37. 2022DiffDock: Diffusion Steps, Twists, and Turns for Molecular Dockingcited by 307
  38. 2020GraphAF: a Flow-based Autoregressive Model for Molecular Graph Generationcited by 301

50 most cited of 93 All 93 (JSON)

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Cited by year (2026 to 7 Oct)

Citing papers per year: 2023: 11; 2024: 12; 2025: 9; 2026: 2.

34 papers.

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  1. 2023MLAgentBench: Evaluating Language Agents on Machine Learning Experimentationcited by 339
  2. 2024Position: Topological Deep Learning is the New Frontier for Relational Learningcited by 65
  3. 2023On the Design Fundamentals of Diffusion Models: A Surveycited by 59
  4. 2023Enhancing Deep Reinforcement Learning: A Tutorial on Generative Diffusion Models in Network Optimizationcited by 56
  5. 2024A Comprehensive Survey on Data Augmentationcited by 38
  6. 2023Segment Anything Model (SAM) Meets Glass: Mirror and Transparent Objects Cannot Be Easily Detectedcited by 34
  7. 2023A Survey on ChatGPT: AI-Generated Contents, Challenges, and Solutionscited by 34
  8. 2024A Survey of Generative AI for de novo Drug Design: New Frontiers in Molecule and Protein Generationcited by 29
  9. 2023SpectralDiff: A Generative Framework for Hyperspectral Image Classification with Diffusion Modelscited by 28
  10. 2024Diffusion Models in textitDe Novo Drug Designcited by 26
  11. 2024Hyperbolic Geometric Latent Diffusion Model for Graph Generationcited by 20
  12. 2024DiffSG: A Generative Solver for Network Optimization with Diffusion Modelcited by 13
22 more
  1. 2024Graph Diffusion Policy Optimizationcited by 12
  2. 2023A Comprehensive Survey on Generative Diffusion Models for Structured Datacited by 7
  3. 2023A Survey of Generative AI for Intelligent Transportation Systems: Road Transportation Perspectivecited by 6
  4. 2024VC dimension of Graph Neural Networks with Pfaffian activation functionscited by 6
  5. 2023Attack-SAM: Towards Attacking Segment Anything Model With Adversarial Examplescited by 5
  6. 2025Rao-Blackwell Gradient Estimators for Equivariant Denoising Diffusioncited by 4
  7. 2024A Literature Review of Literature Reviews in Pattern Analysis and Machine Intelligencecited by 3
  8. 2024Diffusion-based Graph Generative Methodscited by 2
  9. 2026Inference Attacks Against Graph Generative Diffusion Modelscited by 2
  10. 2023On the importance of catalyst-adsorbate 3D interactions for relaxed energy predictionscited by 1
  11. 2025DMol: A Highly Efficient and Chemical Motif-Preserving Molecule Generation Platformcited by 1
  12. 2025Integrating Machine Learning into Belief-Desire-Intention Agents: Current Advances and Open Challengescited by 1
  13. 2023Multi-objective Molecular Optimization for Opioid Use Disorder Treatment Using Generative Network Complexcited by 0
  14. 2024Combinatorial Complex Score-based Diffusion Modelling through Stochastic Differential Equationscited by 0
  15. 2024GUISE: Graph GaUssIan Shading watErmarkcited by 0
  16. 2025Towards Automated Self-Supervised Learning for Truly Unsupervised Graph Anomaly Detectioncited by 0
  17. 2025A Deep Generative Model for the Simulation of Discrete Karst Networkscited by 0
  18. 2025FAROS: Fair Graph Generation via Attribute Switching Mechanismscited by 0
  19. 2025NGTM: Substructure-based Neural Graph Topic Model for Interpretable Graph Generationcited by 0
  20. 2025Look the Other Way: Designing 'Positive' Molecules with Negative Data via Task Arithmeticcited by 0
  21. 2025Cognitive Structure Generation: From Educational Priors to Policy Optimizationcited by 0
  22. 2026Seasoning Generative Models for a Generalization Aftertastecited by 0

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  3. 2025Diffusion Models for Molecules: A Survey of Methods and Tasks
  4. 2024Context-Guided Diffusion for Out-of-Distribution Molecular and Protein Design
  5. 2023Conditional Diffusion Based on Discrete Graph Structures for Molecular Graph Generation
  6. 2023Autoregressive Diffusion Model for Graph Generation
  7. 2025Exploring Molecule Generation Using Latent Space Graph Diffusion
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