mlsanityData to 7 Oct 2026

Glow: Generative Flow with Invertible 1x1 Convolutions

arXiv 1807.03039 ↗First posted 9 Jul 2018stat.ML cs.AI cs.LGcited by 1,539

Not on the map. Why?

Cited by 251 in Diffusion models, but placed by its own abstract, which didn’t fit.

Abstract (arXiv)

Flow-based generative models (Dinh et al., 2014) are conceptually attractive due to tractability of the exact log-likelihood, tractability of exact latent-variable inference, and parallelizability of both training and synthesis. In this paper we propose Glow, a simple type of generative flow using an invertible 1x1 convolution. Using our method we demonstrate a significant improvement in log-likelihood on standard benchmarks. Perhaps most strikingly, we demonstrate that a generative model optimized towards the plain log-likelihood objective is capable of efficient realistic-looking synthesis and manipulation of large images. The code for our model is available at https://github.com/openai/glow

Key facts. Cited by 1,539 papers in the map (data through 7 Oct 2026). First posted on arXiv 9 Jul 2018.

Builds on

No reference list yet.

Built on by

Cited by year (2026 to 7 Oct)

Citing papers per year: 2021: 326; 2022: 313; 2023: 310; 2024: 233; 2025: 206; 2026: 151.

1,539 papers.

Sort:

By area:

  1. 2021High-Resolution Image Synthesis with Latent Diffusion Modelscited by 18,694
  2. 2022Classifier-Free Diffusion Guidancecited by 5,717
  3. 2022Flow Matching for Generative Modelingcited by 5,426
  4. 2021Improved Denoising Diffusion Probabilistic Modelscited by 3,736
  5. 2023Consistency Modelscited by 1,778
  6. 2021Structured Denoising Diffusion Models in Discrete State-Spacescited by 1,665
  7. 2021Image Super-Resolution via Iterative Refinementcited by 1,506
  8. 2021Palette: Image-to-Image Diffusion Modelscited by 1,296
  9. 2021Cascaded Diffusion Models for High Fidelity Image Generationcited by 1,155
  10. 2021Variational Diffusion Modelscited by 1,145
  11. 2022Diffusion Models: A Comprehensive Survey of Methods and Applicationscited by 1,107
  12. 2022Building Normalizing Flows with Stochastic Interpolantscited by 964
38 more
  1. 2021Generalized Out-of-Distribution Detection: A Surveycited by 796
  2. 2021Towards Total Recall in Industrial Anomaly Detectioncited by 772
  3. 2022MotionDiffuse: Text-Driven Human Motion Generation with Diffusion Modelcited by 768
  4. 2021Going deeper with Image Transformerscited by 759
  5. 2021Vector-quantized Image Modeling with Improved VQGANcited by 656
  6. 2021VideoGPT: Video Generation using VQ-VAE and Transformerscited by 651
  7. 2021DiffusionCLIP: Text-Guided Diffusion Models for Robust Image Manipulationcited by 640
  8. 2021Score-based Generative Modeling in Latent Spacecited by 634
  9. 2021ILVR: Conditioning Method for Denoising Diffusion Probabilistic Modelscited by 634
  10. 2021Tackling the Generative Learning Trilemma with Denoising Diffusion GANscited by 515
  11. 2022StyleGAN-XL: Scaling StyleGAN to Large Diverse Datasetscited by 489
  12. 2021Grad-TTS: A Diffusion Probabilistic Model for Text-to-Speechcited by 445
  13. 2023Improved Techniques for Training Consistency Modelscited by 430
  14. 2021SRDiff: Single Image Super-Resolution with Diffusion Probabilistic Modelscited by 415
  15. 2023Voicebox: Text-Guided Multilingual Universal Speech Generation at Scalecited by 373
  16. 2021GAN Inversion: A Surveycited by 366
  17. 2022Analog Bits: Generating Discrete Data using Diffusion Models with Self-Conditioningcited by 362
  18. 2022Analytic-DPM: an Analytic Estimate of the Optimal Reverse Variance in Diffusion Probabilistic Modelscited by 331
  19. 2023Make-An-Audio: Text-To-Audio Generation with Prompt-Enhanced Diffusion Modelscited by 323
  20. 2021Self-Supervised Learning with Data Augmentations Provably Isolates Content from Stylecited by 308
  21. 2022Perception Prioritized Training of Diffusion Modelscited by 301
  22. 2023Understanding Diffusion Objectives as the ELBO with Simple Data Augmentationcited by 293
  23. 2021SSD: A Unified Framework for Self-Supervised Outlier Detectioncited by 264
  24. 2021Generating Images with Sparse Representationscited by 262
  25. 2022EDICT: Exact Diffusion Inversion via Coupled Transformationscited by 256
  26. 2021CLIP-Forge: Towards Zero-Shot Text-to-Shape Generationcited by 254
  27. 2021Deep Generative Modelling: A Comparative Review of VAEs, GANs, Normalizing Flows, Energy-Based and Autoregressive Modelscited by 251
  28. 2021Pre-training Molecular Graph Representation with 3D Geometrycited by 248
  29. 2023Self-Consuming Generative Models Go MADcited by 239
  30. 2023Diff-Instruct: A Universal Approach for Transferring Knowledge From Pre-trained Diffusion Modelscited by 232
  31. 2021Score-Based Generative Modeling with Critically-Damped Langevin Diffusioncited by 230
  32. 2021FastFlow: Unsupervised Anomaly Detection and Localization via 2D Normalizing Flowscited by 225
  33. 2022BBDM: Image-to-image Translation with Brownian Bridge Diffusion Modelscited by 222
  34. 2022CDDFuse: Correlation-Driven Dual-Branch Feature Decomposition for Multi-Modality Image Fusioncited by 222
  35. 2022The Role of ImageNet Classes in Fr'echet Inception Distancecited by 211
  36. 2021Projected GANs Converge Fastercited by 204
  37. 2021PIRenderer: Controllable Portrait Image Generation via Semantic Neural Renderingcited by 202
  38. 2022Continuous diffusion for categorical datacited by 202

50 most cited of 1,539 All 1,539 (JSON)