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Improving GANs Using Optimal Transport

arXiv 1803.05573 ↗First posted 15 Mar 2018cs.LG stat.MLcited by 122

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Abstract (arXiv)

We present Optimal Transport GAN (OT-GAN), a variant of generative adversarial nets minimizing a new metric measuring the distance between the generator distribution and the data distribution. This metric, which we call mini-batch energy distance, combines optimal transport in primal form with an energy distance defined in an adversarially learned feature space, resulting in a highly discriminative distance function with unbiased mini-batch gradients. Experimentally we show OT-GAN to be highly stable when trained with large mini-batches, and we present state-of-the-art results on several popular benchmark problems for image generation.

Key facts. Cited by 122 papers in the map (data through 7 Oct 2026). First posted on arXiv 15 Mar 2018.

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Citing papers per year: 2020: 2; 2021: 27; 2022: 27; 2023: 28; 2024: 17; 2025: 17; 2026: 4.

122 papers.

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  1. 2021Cross-Modal Contrastive Learning for Text-to-Image Generationcited by 259
  2. 2023SE(3)-Stochastic Flow Matching for Protein Backbone Generationcited by 147
  3. 2023Ambiguous Medical Image Segmentation using Diffusion Modelscited by 92
  4. 2021Proximal Optimal Transport Modeling of Population Dynamicscited by 91
  5. 2023Simulation-free Schr"odinger bridges via score and flow matchingcited by 81
  6. 2022PLOT: Prompt Learning with Optimal Transport for Vision-Language Modelscited by 64
  7. 2021Minibatch optimal transport distances; analysis and applicationscited by 62
  8. 2022Generative Multiplane Images: Making a 2D GAN 3D-Awarecited by 57
  9. 2021Don't Generate Me: Training Differentially Private Generative Models with Sinkhorn Divergencecited by 54
  10. 2021Rates of Estimation of Optimal Transport Maps using Plug-in Estimators via Barycentric Projectionscited by 52
  11. 2023Effective Neural Topic Modeling with Embedding Clustering Regularizationcited by 46
  12. 2022Unbalanced Optimal Transport, from Theory to Numericscited by 45
38 more
  1. 2021Improving Mini-batch Optimal Transport via Partial Transportationcited by 40
  2. 2023SoK: Privacy-Preserving Data Synthesiscited by 37
  3. 2021A Survey on Optimal Transport for Machine Learning: Theory and Applicationscited by 35
  4. 2021Data Efficient Language-supervised Zero-shot Recognition with Optimal Transport Distillationcited by 35
  5. 2024FASTopic: Pretrained Transformer is a Fast, Adaptive, Stable, and Transferable Topic Modelcited by 34
  6. 2023The Monge Gap: A Regularizer to Learn All Transport Mapscited by 32
  7. 2020Imitation Learning with Sinkhorn Distancescited by 30
  8. 2022A Unified Framework for Implicit Sinkhorn Differentiationcited by 28
  9. 2024AWT: Transferring Vision-Language Models via Augmentation, Weighting, and Transportationcited by 27
  10. 2025Distributional Diffusion Models with Scoring Rulescited by 25
  11. 2022A Survey on Training Challenges in Generative Adversarial Networks for Biomedical Image Analysiscited by 24
  12. 2022Hierarchical Sliced Wasserstein Distancecited by 23
  13. 2023Quasi-Monte Carlo for 3D Sliced Wassersteincited by 22
  14. 2022Optimal transport map estimation in general function spacescited by 20
  15. 2023Sampling via Gradient Flows in the Space of Probability Measurescited by 20
  16. 2024Tyche: Stochastic In-Context Learning for Medical Image Segmentationcited by 20
  17. 2026Sinkhorn-Drifting Generative Modelscited by 20
  18. 2022AADG: Automatic Augmentation for Domain Generalization on Retinal Image Segmentationcited by 18
  19. 2024On the Affinity, Rationality, and Diversity of Hierarchical Topic Modelingcited by 18
  20. 2021Input Convex Gradient Networkscited by 17
  21. 2022Amortized Projection Optimization for Sliced Wasserstein Generative Modelscited by 17
  22. 2022Taming Hyperparameter Tuning in Continuous Normalizing Flows Using the JKO Schemecited by 17
  23. 2026Generative Drifting is Secretly Score Matching: a Spectral and Variational Perspectivecited by 17
  24. 2021Large-scale optimal transport map estimation using projection pursuitcited by 16
  25. 2023Monge, Bregman and Occam: Interpretable Optimal Transport in High-Dimensions with Feature-Sparse Mapscited by 16
  26. 2023Performance Scaling via Optimal Transport: Enabling Data Selection from Partially Revealed Sourcescited by 16
  27. 2023OST: Refining Text Knowledge with Optimal Spatio-Temporal Descriptor for General Video Recognitioncited by 16
  28. 2021On Transportation of Mini-batches: A Hierarchical Approachcited by 15
  29. 2023Improving Cross-lingual Information Retrieval on Low-Resource Languages via Optimal Transport Distillationcited by 15
  30. 2024Sliced Wasserstein with Random-Path Projecting Directionscited by 15
  31. 2022Rethinking Initialization of the Sinkhorn Algorithmcited by 14
  32. 2021Entropic Gromov-Wasserstein between Gaussian Distributionscited by 12
  33. 2021Near-optimal estimation of smooth transport maps with kernel sums-of-squarescited by 12
  34. 2023Markovian Sliced Wasserstein Distances: Beyond Independent Projectionscited by 11
  35. 2023Flow Factorized Representation Learningcited by 11
  36. 2023Sample Complexity Bounds for Estimating Probability Divergences under Invariancescited by 11
  37. 2021Re-evaluating Word Mover's Distancecited by 10
  38. 2021Entropy Regularized Optimal Transport Independence Criterioncited by 9

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