mlsanityData to 14 Oct 2026

Metropolis-Hastings Generative Adversarial Networks

arXiv 1811.11357 ↗First posted 28 Nov 2018stat.ML cs.LGcited by 41

Not on the map. Why?

Abstract (arXiv)

We introduce the Metropolis-Hastings generative adversarial network (MH-GAN), which combines aspects of Markov chain Monte Carlo and GANs. The MH-GAN draws samples from the distribution implicitly defined by a GAN's discriminator-generator pair, as opposed to standard GANs which draw samples from the distribution defined only by the generator. It uses the discriminator from GAN training to build a wrapper around the generator for improved sampling. With a perfect discriminator, this wrapped generator samples from the true distribution on the data exactly even when the generator is imperfect. We demonstrate the benefits of the improved generator on multiple benchmark datasets, including CIFAR-10 and CelebA, using the DCGAN, WGAN, and progressive GAN.

Key facts. Cited by 41 papers in the map (data through 14 Oct 2026). First posted on arXiv 28 Nov 2018.

Builds on

No reference list yet.

Built on by

Cited by year (2026 to 14 Oct)

Citing papers per year: 2020: 1; 2021: 13; 2022: 5; 2023: 6; 2024: 4; 2025: 6; 2026: 6.

41 papers.

Sort:

By area:

  1. 2023Extracting Training Data from Diffusion Modelscited by 732
  2. 2021Deep Generative Modelling: A Comparative Review of VAEs, GANs, Normalizing Flows, Energy-Based and Autoregressive Modelscited by 252
  3. 2023Exposing flaws of generative model evaluation metrics and their unfair treatment of diffusion modelscited by 205
  4. 2022High-Resolution Virtual Try-On with Misalignment and Occlusion-Handled Conditionscited by 130
  5. 2022Refining Generative Process with Discriminator Guidance in Score-based Diffusion Modelscited by 100
  6. 2023KL Convergence Guarantees for Score diffusion models under minimal data assumptionscited by 63
  7. 2024Stochastic Localization via Iterative Posterior Samplingcited by 28
  8. 2023Cousins Of The Vendi Score: A Family Of Similarity-Based Diversity Metrics For Science And Machine Learningcited by 24
  9. 2021Local-Global MCMC kernels: the best of both worldscited by 22
  10. 2022Polarity Sampling: Quality and Diversity Control of Pre-Trained Generative Networks via Singular Valuescited by 21
  11. 2021Self-Diagnosing GAN: Diagnosing Underrepresented Samples in Generative Adversarial Networkscited by 13
  12. 2024Diffusion Rejection Samplingcited by 11
29 more
  1. 2021BIGRoC: Boosting Image Generation via a Robust Classifiercited by 9
  2. 2021Model Extraction and Defenses on Generative Adversarial Networkscited by 8
  3. 2022Semi-Supervised Manifold Learning with Complexity Decoupled Chart Autoencoderscited by 8
  4. 2021Latent reweighting, an almost free improvement for GANscited by 6
  5. 2023Discriminator Guidance for Autoregressive Diffusion Modelscited by 5
  6. 2023Optimal Budgeted Rejection Sampling for Generative Modelscited by 5
  7. 2024Multi-objective evolutionary GAN for tabular data synthesiscited by 5
  8. 2025The Vendiscope: An Algorithmic Microscope For Data Collectionscited by 5
  9. 2025DeBackdoor: A Deductive Framework for Detecting Backdoor Attacks on Deep Models with Limited Datacited by 5
  10. 2021Mitigating Statistical Bias within Differentially Private Synthetic Datacited by 4
  11. 2020oIRL: Robust Adversarial Inverse Reinforcement Learning with Temporally Extended Actionscited by 3
  12. 2021Black-Box Diagnosis and Calibration on GAN Intra-Mode Collapse: A Pilot Studycited by 3
  13. 2021Reparameterized Sampling for Generative Adversarial Networkscited by 2
  14. 2024Denoising Diffusion-Based Control of Nonlinear Systemscited by 2
  15. 2025Score Matching Diffusion Based Feedback Control and Planning of Nonlinear Systemscited by 2
  16. 2021NEO: Non Equilibrium Sampling on the Orbit of a Deterministic Transformcited by 1
  17. 2022Mining Multi-Label Samples from Single Positive Labelscited by 1
  18. 2025Studying Classifier(-Free) Guidance From a Classifier-Centric Perspectivecited by 1
  19. 2025Enhanced Generative Model Evaluation with Clipped Density and Coveragecited by 1
  20. 2026Curriculum Group Policy Optimization: Adaptive Sampling for Unleashing the Potential of Text-to-Image Generationcited by 1
  21. 2021Variational Rejection Particle Filteringcited by 0
  22. 2021Deep Probabilistic Graphical Modelingcited by 0
  23. 2021On the Performance Analysis of the Adversarial System Variant Approximation Method to Quantify Process Model Generalizationcited by 0
  24. 2025EPR-GAIL: An EPR-Enhanced Hierarchical Imitation Learning Framework to Simulate Complex User Consumption Behaviorscited by 0
  25. 2026GICDM: Mitigating Hubness for Reliable Distance-Based Generative Model Evaluationcited by 0
  26. 2026Bayesian Generative Adversarial Networks via Gaussian Approximation for Tabular Data Synthesiscited by 0
  27. 2026Total Variation Guarantees for Sampling with Stochastic Localizationcited by 0
  28. 2026Enhanced Low-Density Region Exploration in Classifier-Guided Diffusion Models Through Modified Reverse Diffusion Samplingcited by 0
  29. 2026Radial Tail Repair: Post-Training Correction for Diffusion and Flow Modelscited by 0