Analyzing and Improving Optimal-Transport-based Adversarial Networks
Not on the map. Why?
Abstract (arXiv)
Optimal Transport (OT) problem aims to find a transport plan that bridges two distributions while minimizing a given cost function. OT theory has been widely utilized in generative modeling. In the beginning, OT distance has been used as a measure for assessing the distance between data and generated distributions. Recently, OT transport map between data and prior distributions has been utilized as a generative model. These OT-based generative models share a similar adversarial training objective. In this paper, we begin by unifying these OT-based adversarial methods within a single framework. Then, we elucidate the role of each component in training dynamics through a comprehensive analysis of this unified framework. Moreover, we suggest a simple but novel method that improves the previously best-performing OT-based model. Intuitively, our approach conducts a gradual refinement of the generated distribution, progressively aligning it with the data distribution. Our approach achieves a FID score of 2.51 on CIFAR-10 and 5.99 on CelebA-HQ-256, outperforming unified OT-based adversarial approaches.
Key facts. Cited by 8 papers in the map (data through 7 Oct 2026). Builds on 53 of its 69 references that are in the map. First posted on arXiv 4 Oct 2023.
Builds on
53 of 69 references.
References · 53
- 2020Denoising Diffusion Probabilistic Modelscited by 20,851
- 2020Denoising Diffusion Implicit Modelscited by 9,655
- 2020Score-Based Generative Modeling through Stochastic Differential Equationscited by 8,964
- 2018A Style-Based Generator Architecture for Generative Adversarial Networkscited by 5,986
- 2022Generative Adversarial Networkscited by 5,603
- 2016SGDR: Stochastic Gradient Descent with Warm Restartscited by 4,993
- 2019Generative Modeling by Estimating Gradients of the Data Distributioncited by 4,067
- 2020Taming Transformers for High-Resolution Image Synthesiscited by 3,229
- 2017Progressive Growing of GANs for Improved Quality, Stability, and Variationcited by 2,967
- 2016Improved Techniques for Training GANscited by 2,938
- 2017Improved Training of Wasserstein GANscited by 2,223
- 2015Unsupervised Representation Learning with Deep Convolutional Generative Adversarial Networkscited by 2,048
38 more
- 2018Spectral Normalization for Generative Adversarial Networkscited by 1,618
- 2018Glow: Generative Flow with Invertible 1x1 Convolutionscited by 1,539
- 2020Training Generative Adversarial Networks with Limited Datacited by 1,184
- 2019Improved Precision and Recall Metric for Assessing Generative Modelscited by 925
- 2016Pixel Recurrent Neural Networkscited by 814
- 2018Computational Optimal Transportcited by 765
- 2018Which Training Methods for GANs do actually Converge?cited by 672
- 2020NVAE: A Deep Hierarchical Variational Autoencodercited by 635
- 2021Score-based Generative Modeling in Latent Spacecited by 634
- 2021Tackling the Generative Learning Trilemma with Denoising Diffusion GANscited by 515
- 2015Optimal Transport for Domain Adaptationcited by 457
- 2021Score-Based Generative Modeling with Critically-Damped Langevin Diffusioncited by 230
- 2019Optimal transport mapping via input convex neural networkscited by 202
- 2020Geometric Dataset Distances via Optimal Transportcited by 157
- 2020Adversarial Latent Autoencoderscited by 155
- 2021StyleSwin: Transformer-based GAN for High-resolution Image Generationcited by 152
- 2015Optimal Entropy-Transport problems and a new Hellinger-Kantorovich distance between positive measurescited by 138
- 2021Unbalanced minibatch Optimal Transport; applications to Domain Adaptationcited by 123
- 2022Neural Optimal Transportcited by 123
- 2020Learning Energy-Based Models by Diffusion Recovery Likelihoodcited by 122
- 2017Stabilizing Training of Generative Adversarial Networks through Regularizationcited by 118
- 2020VAEBM: A Symbiosis between Variational Autoencoders and Energy-based Modelscited by 103
- 2019AutoGAN: Neural Architecture Search for Generative Adversarial Networkscited by 94
- 2020Robust Optimal Transport with Applications in Generative Modeling and Domain Adaptationcited by 86
- 2021Generative Modeling with Optimal Transport Mapscited by 80
- 2022Subspace Diffusion Generative Modelscited by 70
- 2017Gradient descent GAN optimization is locally stablecited by 65
- 2017On the regularization of Wasserstein GANscited by 65
- 2020A Contrastive Learning Approach for Training Variational Autoencoder Priorscited by 65
- 2020Dual Contradistinctive Generative Autoencodercited by 58
- 2018On the Convergence and Robustness of Training GANs with Regularized Optimal Transportcited by 51
- 2020Refining Deep Generative Models via Discriminator Gradient Flowcited by 45
- 2018Scalable Unbalanced Optimal Transport using Generative Adversarial Networkscited by 41
- 2022Can Push-forward Generative Models Fit Multimodal Distributions?cited by 41
- 2023Generative Modeling through the Semi-dual Formulation of Unbalanced Optimal Transportcited by 39
- 2019On Scalable and Efficient Computation of Large Scale Optimal Transportcited by 29
- 2018Disconnected Manifold Learning for Generative Adversarial Networkscited by 27
- 2018Is Generator Conditioning Causally Related to GAN Performance?cited by 18
50 most cited of 53 All 53 (JSON)
Built on by
Citing papers per year: 2024: 4; 2025: 2; 2026: 2.
8 papers.
- 2024Robust Barycenter Estimation using Semi-Unbalanced Neural Optimal Transportcited by 9
- 2024Improving Neural Optimal Transport via Displacement Interpolationcited by 7
- 2025Overcoming Spurious Solutions in Semi-Dual Neural Optimal Transport: A Smoothing Approach for Learning the Optimal Transport Plancited by 6
- 2024Scalable Simulation-free Entropic Unbalanced Optimal Transportcited by 5
- 2025A Statistical Learning Perspective on Semi-dual Adversarial Neural Optimal Transport Solverscited by 2
- 2024Unsupervised Point Cloud Completion through Unbalanced Optimal Transportcited by 1
- 2026Conditional Unbalanced Optimal Transport Maps: An Outlier-Robust Framework for Conditional Generative Modelingcited by 0
- 2026UOTIP: Unbalanced Optimal Transport Map for Unpaired Inverse Problemscited by 0
- 2026UOTIP: Unbalanced Optimal Transport Map for Unpaired Inverse Problems20 May 2026
- 2026Conditional Unbalanced Optimal Transport Maps: An Outlier-Robust Framework for Conditional Generative Modeling7 Mar 2026
- 2025Overcoming Spurious Solutions in Semi-Dual Neural Optimal Transport: A Smoothing Approach for Learning the Optimal Transport Plan7 Feb 2025
- 2025A Statistical Learning Perspective on Semi-dual Adversarial Neural Optimal Transport Solvers3 Feb 2025
- 2024Robust Barycenter Estimation using Semi-Unbalanced Neural Optimal Transport4 Oct 2024
- 2024Improving Neural Optimal Transport via Displacement Interpolation3 Oct 2024
- 2024Unsupervised Point Cloud Completion through Unbalanced Optimal Transport3 Oct 2024
- 2024Scalable Simulation-free Entropic Unbalanced Optimal Transport3 Oct 2024