mlsanityData to 7 Oct 2026

A Review on Generative Adversarial Networks: Algorithms, Theory, and Applications

arXiv 2001.06937 ↗First posted 20 Jan 2020cs.LG stat.MLcited by 209

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Cited by 23 in Diffusion models, but placed by its own abstract, which didn’t fit.

Abstract (arXiv)

Generative adversarial networks (GANs) are a hot research topic recently. GANs have been widely studied since 2014, and a large number of algorithms have been proposed. However, there is few comprehensive study explaining the connections among different GANs variants, and how they have evolved. In this paper, we attempt to provide a review on various GANs methods from the perspectives of algorithms, theory, and applications. Firstly, the motivations, mathematical representations, and structure of most GANs algorithms are introduced in details. Furthermore, GANs have been combined with other machine learning algorithms for specific applications, such as semi-supervised learning, transfer learning, and reinforcement learning. This paper compares the commonalities and differences of these GANs methods. Secondly, theoretical issues related to GANs are investigated. Thirdly, typical applications of GANs in image processing and computer vision, natural language processing, music, speech and audio, medical field, and data science are illustrated. Finally, the future open research problems for GANs are pointed out.

Key facts. Cited by 209 papers in the map (data through 7 Oct 2026). First posted on arXiv 20 Jan 2020.

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Cited by year (2026 to 7 Oct)

Citing papers per year: 2021: 37; 2022: 35; 2023: 61; 2024: 32; 2025: 35; 2026: 9.

209 papers.

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  1. 2022Diffusion Models: A Comprehensive Survey of Methods and Applicationscited by 1,107
  2. 2024Retrieval-Augmented Generation for AI-Generated Content: A Surveycited by 352
  3. 2021Deep Generative Modelling: A Comparative Review of VAEs, GANs, Normalizing Flows, Energy-Based and Autoregressive Modelscited by 251
  4. 2022Diffusion Probabilistic Modeling for Video Generationcited by 237
  5. 2023A Survey on Self-supervised Learning: Algorithms, Applications, and Future Trendscited by 205
  6. 2021TransGAN: Two Pure Transformers Can Make One Strong GAN, and That Can Scale Upcited by 162
  7. 2024RGBleftrightarrowX: Image decomposition and synthesis using material- and lighting-aware diffusion modelscited by 159
  8. 2023State of the Art on Diffusion Models for Visual Computingcited by 126
  9. 2021Robust Learning Meets Generative Models: Can Proxy Distributions Improve Adversarial Robustness?cited by 113
  10. 2023Monte Carlo guided Diffusion for Bayesian linear inverse problemscited by 65
  11. 2024Advances in 3D Generation: A Surveycited by 62
  12. 2023Enhancing Deep Reinforcement Learning: A Tutorial on Generative Diffusion Models in Network Optimizationcited by 56
38 more
  1. 2021ImGAGN:Imbalanced Network Embedding via Generative Adversarial Graph Networkscited by 51
  2. 2025Text2Earth: Unlocking Text-driven Remote Sensing Image Generation with a Global-Scale Dataset and a Foundation Modelcited by 46
  3. 2022Recent Advances for Quantum Neural Networks in Generative Learningcited by 39
  4. 2021Image2Reverb: Cross-Modal Reverb Impulse Response Synthesiscited by 34
  5. 2022A Review of Emerging Research Directions in Abstract Visual Reasoningcited by 33
  6. 2023Deep Incomplete Multi-view Clustering with Cross-view Partial Sample and Prototype Alignmentcited by 33
  7. 2023Synthetic CT Generation from MRI using 3D Transformer-based Denoising Diffusion Modelcited by 29
  8. 2023Bayesian Conditional Diffusion Models for Versatile Spatiotemporal Turbulence Generationcited by 28
  9. 2022Generative machine learning methods for multivariate ensemble post-processingcited by 26
  10. 2021Data-Efficient GAN Training Beyond (Just) Augmentations: A Lottery Ticket Perspectivecited by 25
  11. 2021Wavelet-Packets for Deepfake Image Analysis and Detectioncited by 25
  12. 2025A Survey on Human Interaction Motion Generationcited by 25
  13. 2021Explainable Reinforcement Learning for Broad-XAI: A Conceptual Framework and Surveycited by 24
  14. 2022A Survey on Training Challenges in Generative Adversarial Networks for Biomedical Image Analysiscited by 24
  15. 2022AdvMIL: Adversarial Multiple Instance Learning for the Survival Analysis on Whole-Slide Imagescited by 24
  16. 2023Reliable Generation of Privacy-preserving Synthetic Electronic Health Record Time Series via Diffusion Modelscited by 24
  17. 2024Generative AI for Visualization: State of the Art and Future Directionscited by 23
  18. 2021Creativity and Machine Learning: A Surveycited by 21
  19. 2021Generative adversarial networks in time series: A survey and taxonomycited by 20
  20. 2022A Comprehensive Survey on Data-Efficient GANs in Image Generationcited by 20
  21. 2022Optimal transport map estimation in general function spacescited by 20
  22. 2024A Survey on Statistical Theory of Deep Learning: Approximation, Training Dynamics, and Generative Modelscited by 20
  23. 2021Two-stage Training for Learning from Label Proportionscited by 19
  24. 2021A Comprehensive Survey and Taxonomy on Single Image Dehazing Based on Deep Learningcited by 19
  25. 2021Quaternion Generative Adversarial Networkscited by 17
  26. 2023Generative AI for Physical Layer Communications: A Surveycited by 17
  27. 2022Multi-Label Clinical Time-Series Generation via Conditional GANcited by 16
  28. 2021Applications of Generative Adversarial Networks in Anomaly Detection: A Systematic Literature Reviewcited by 15
  29. 2022A survey on GANs for computer vision: Recent research, analysis and taxonomycited by 15
  30. 2023Ten Years of Generative Adversarial Nets (GANs): A survey of the state-of-the-artcited by 14
  31. 2024A Practical Guide to Sample-based Statistical Distances for Evaluating Generative Models in Sciencecited by 14
  32. 2021An overview of artificial intelligence techniques for diagnosis of Schizophrenia based on magnetic resonance imaging modalities: Methods, challenges, and future workscited by 13
  33. 2021A review of Generative Adversarial Networks (GANs) and its applications in a wide variety of disciplines -- From Medical to Remote Sensingcited by 13
  34. 2023Bayesian Renormalizationcited by 13
  35. 2024textitTrans-LoRA: towards data-free Transferable Parameter Efficient Finetuningcited by 13
  36. 2024Enhancing Diagnostic Accuracy in Rare and Common Fundus Diseases with a Knowledge-Rich Vision-Language Modelcited by 12
  37. 2022Learning with Asymmetric Kernels: Least Squares and Feature Interpretationcited by 11
  38. 2022Assessing the ability of generative adversarial networks to learn canonical medical image statisticscited by 11

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