mlsanityData to 14 Oct 2026

Generative Adversarial Nets from a Density Ratio Estimation Perspective

arXiv 1610.02920 ↗First posted 10 Oct 2016stat.MLcited by 24

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Abstract (arXiv)

Generative adversarial networks (GANs) are successful deep generative models. GANs are based on a two-player minimax game. However, the objective function derived in the original motivation is changed to obtain stronger gradients when learning the generator. We propose a novel algorithm that repeats the density ratio estimation and f-divergence minimization. Our algorithm offers a new perspective toward the understanding of GANs and is able to make use of multiple viewpoints obtained in the research of density ratio estimation, e.g. what divergence is stable and relative density ratio is useful.

Key facts. Cited by 24 papers in the map (data through 14 Oct 2026). First posted on arXiv 10 Oct 2016.

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Citing papers per year: 2021: 7; 2022: 5; 2023: 2; 2024: 5; 2025: 5.

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  1. 2021A Theory of Label Propagation for Subpopulation Shiftcited by 48
  2. 2021Near-Optimal Linear Regression under Distribution Shiftcited by 42
  3. 2024Training Unbiased Diffusion Models From Biased Datasetcited by 25
  4. 2025Target Concrete Score Matching: A Holistic Framework for Discrete Diffusioncited by 25
  5. 2022A General Recipe for Likelihood-free Bayesian Optimizationcited by 19
  6. 2023MonoFlow: Rethinking Divergence GANs via the Perspective of Wasserstein Gradient Flowscited by 13
  7. 2025Zero-Shot Adaptation of Behavioral Foundation Models to Unseen Dynamicscited by 8
  8. 2021Meta-Learning for Relative Density-Ratio Estimationcited by 6
  9. 2022Forget-me-not! Contrastive Critics for Mitigating Posterior Collapsecited by 6
  10. 2021A Unified Framework for Multi-distribution Density Ratio Estimationcited by 5
  11. 2023Machine Learning and the Future of Bayesian Computationcited by 4
  12. 2024Optimal Aggregation of Prediction Intervals under Unsupervised Domain Shiftcited by 4
12 more
  1. 2021F-Divergences and Cost Function Locality in Generative Modelling with Quantum Circuitscited by 3
  2. 2021Continual Density Ratio Estimation in an Online Settingcited by 2
  3. 2021Improving Bridge estimators via f-GANcited by 2
  4. 2024Bounds on Lp errors in density ratio estimation via f-divergence loss functionscited by 2
  5. 2025Improving Discriminator Guidance in Diffusion Modelscited by 2
  6. 2022A Unified f-divergence Framework Generalizing VAE and GANcited by 1
  7. 2022Generalized Balancing Weights via Deep Neural Networkscited by 1
  8. 2024Alpha-divergence loss function for neural density ratio estimationcited by 1
  9. 2022Unified Perspective on Probability Divergence via Maximum Likelihood Density Ratio Estimation: Bridging KL-Divergence and Integral Probability Metricscited by 0
  10. 2024A density ratio framework for evaluating the utility of synthetic datacited by 0
  11. 2025Boosting Statistic Learning with Synthetic Data from Pretrained Large Modelscited by 0
  12. 2025Discriminative classification with generative features: bridging Naive Bayes and logistic regressioncited by 0