mlsanityData to 7 Oct 2026

Graphite: Iterative Generative Modeling of Graphs

arXiv 1803.10459 ↗First posted 28 Mar 2018stat.ML cs.LG cs.NEcited by 112

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Abstract (arXiv)

Graphs are a fundamental abstraction for modeling relational data. However, graphs are discrete and combinatorial in nature, and learning representations suitable for machine learning tasks poses statistical and computational challenges. In this work, we propose Graphite, an algorithmic framework for unsupervised learning of representations over nodes in large graphs using deep latent variable generative models. Our model parameterizes variational autoencoders (VAE) with graph neural networks, and uses a novel iterative graph refinement strategy inspired by low-rank approximations for decoding. On a wide variety of synthetic and benchmark datasets, Graphite outperforms competing approaches for the tasks of density estimation, link prediction, and node classification. Finally, we derive a theoretical connection between message passing in graph neural networks and mean-field variational inference.

Key facts. Cited by 112 papers in the map (data through 7 Oct 2026). First posted on arXiv 28 Mar 2018.

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Citing papers per year: 2020: 1; 2021: 26; 2022: 27; 2023: 25; 2024: 18; 2025: 9; 2026: 6.

112 papers.

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  1. 2021E(n) Equivariant Graph Neural Networkscited by 951
  2. 2021Score-based Generative Modeling in Latent Spacecited by 634
  3. 2022Score-based Generative Modeling of Graphs via the System of Stochastic Differential Equationscited by 273
  4. 2020Permutation Invariant Graph Generation via Score-Based Generative Modelingcited by 263
  5. 2021D'ya like DAGs? A Survey on Structure Learning and Causal Discoverycited by 209
  6. 2021Adversarial Graph Augmentation to Improve Graph Contrastive Learningcited by 200
  7. 2021D2C: Diffusion-Denoising Models for Few-shot Conditional Generationcited by 96
  8. 2021Iterative Refinement Graph Neural Network for Antibody Sequence-Structure Co-designcited by 82
  9. 2023Autoregressive Diffusion Model for Graph Generationcited by 82
  10. 2021ExplaGraphs: An Explanation Graph Generation Task for Structured Commonsense Reasoningcited by 58
  11. 2022Multimodal learning with graphscited by 54
  12. 2022CLEAR: Generative Counterfactual Explanations on Graphscited by 48
38 more
  1. 2021The Future is not One-dimensional: Complex Event Schema Induction by Graph Modeling for Event Predictioncited by 39
  2. 2023Efficient and Scalable Graph Generation through Iterative Local Expansioncited by 35
  3. 2023A Survey on Graph Diffusion Models: Generative AI in Science for Molecule, Protein and Materialcited by 34
  4. 2023Graph Positional and Structural Encodercited by 31
  5. 2022Graph Auto-Encoder Via Neighborhood Wasserstein Reconstructioncited by 28
  6. 2024Unifying Generation and Prediction on Graphs with Latent Graph Diffusioncited by 24
  7. 2021Permutation-Invariant Variational Autoencoder for Graph-Level Representation Learningcited by 23
  8. 2021Unconditional Scene Graph Generationcited by 22
  9. 2022Modularity-Aware Graph Autoencoders for Joint Community Detection and Link Predictioncited by 22
  10. 2022Graph Neural Networks for Moleculescited by 21
  11. 2022NVDiff: Graph Generation through the Diffusion of Node Vectorscited by 18
  12. 2023Deep Generative Models for Detector Signature Simulation: A Taxonomic Reviewcited by 18
  13. 2021Deconvolutional Networks on Graph Datacited by 16
  14. 2022Interpretable Molecular Graph Generation via Monotonic Constraintscited by 15
  15. 2023Improving Graph Generation by Restricting Graph Bandwidthcited by 15
  16. 2023A Simple and Scalable Representation for Graph Generationcited by 15
  17. 2025Generative Models in Decision Making: A Surveycited by 14
  18. 2021On the Power of Edge Independent Graph Modelscited by 13
  19. 2021Cold Start Similar Artists Ranking with Gravity-Inspired Graph Autoencoderscited by 12
  20. 2022Disentangled Spatiotemporal Graph Generative Modelscited by 12
  21. 2022A General Learning Framework for Open Ad Hoc Teamwork Using Graph-based Policy Learningcited by 12
  22. 2023FairGen: Towards Fair Graph Generationcited by 12
  23. 2023A Comprehensive Review of Community Detection in Graphscited by 12
  24. 2024Graph Diffusion Policy Optimizationcited by 12
  25. 2021X-GGM: Graph Generative Modeling for Out-of-Distribution Generalization in Visual Question Answeringcited by 10
  26. 2022Decoupled Self-supervised Learning for Non-Homophilous Graphscited by 10
  27. 2021GraphGen-Redux: a Fast and Lightweight Recurrent Model for labeled Graph Generationcited by 9
  28. 2023Node-Aligned Graph-to-Graph (NAG2G): Elevating Template-Free Deep Learning Approaches in Single-Step Retrosynthesiscited by 9
  29. 2022Explanation Graph Generation via Pre-trained Language Models: An Empirical Study with Contrastive Learningcited by 8
  30. 2022Micro and Macro Level Graph Modeling for Graph Variational Auto-Encoderscited by 8
  31. 2023Cross-Gate MLP with Protein Complex Invariant Embedding is A One-Shot Antibody Designercited by 8
  32. 2024Generating Graphs via Spectral Diffusioncited by 8
  33. 20243M-Diffusion: Latent Multi-Modal Diffusion for Language-Guided Molecular Structure Generationcited by 8
  34. 2022Graph Generative Model for Benchmarking Graph Neural Networkscited by 6
  35. 2022A Framework for Large Scale Synthetic Graph Dataset Generationcited by 5
  36. 2022GraphPNAS: Learning Distribution of Good Neural Architectures via Deep Graph Generative Modelscited by 5
  37. 2024Efficient Dynamic Attributed Graph Generationcited by 5
  38. 2025Graph Guided Diffusion: Unified Guidance for Conditional Graph Generationcited by 5

50 most cited of 112 All 112 (JSON)