mlsanityData to 14 Oct 2026

DPOT: A DeepParticle method for Computation of Optimal Transport with convergence guarantee

arXiv 2506.23429 ↗First posted 29 Jun 2025stat.ML cs.LGcited by 1

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Abstract (arXiv)

In this work, we propose a novel machine learning approach to compute the optimal transport map between two continuous distributions from their unpaired samples, based on the DeepParticle methods. The proposed method leads to a min-min optimization during training and does not impose any restriction on the network structure. Theoretically we establish a weak convergence guarantee and a quantitative error bound between the learned map and the optimal transport map. Our numerical experiments validate the theoretical results and the effectiveness of the new approach, particularly on real-world tasks.

Key facts. Cited by 1 paper in the map (data through 14 Oct 2026). Builds on 21 of its 45 references that are in the map. First posted on arXiv 29 Jun 2025.

Builds on

21 of 45 references.

References · 21

  1. 2015Deep Residual Learning for Image Recognitioncited by 52,096
  2. 2013Sinkhorn Distances: Lightspeed Computation of Optimal Transportation Distancescited by 2,316
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  10. 2023Optimal Transport for Offline Imitation Learningcited by 42
  11. 2021Neural Monge Map estimation and its applicationscited by 40
  12. 2019On the Efficiency of Entropic Regularized Algorithms for Optimal Transportcited by 35
9 more
  1. 2023Energy-guided Entropic Neural Optimal Transportcited by 26
  2. 2023Global Adaptation meets Local Generalization: Unsupervised Domain Adaptation for 3D Human Pose Estimationcited by 19
  3. 2019On a Combination of Alternating Minimization and Nesterov's Momentumcited by 18
  4. 2021DeepParticle: learning invariant measure by a deep neural network minimizing Wasserstein distance on data generated from an interacting particle methodcited by 9
  5. 2019Mode Collapse and Regularity of Optimal Transportation Mapscited by 5
  6. 2018Anomaly detection with Wasserstein GANcited by 4
  7. 2022Randomized methods for computing optimal transport without regularization and their convergence analysiscited by 3
  8. 2022A DeepParticle method for learning and generating aggregation patterns in multi-dimensional Keller-Segel chemotaxis systemscited by 2
  9. 2023Self-reinforced polynomial approximation methods for concentrated probability densitiescited by 2

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Cited by year

Citing papers per year: 2025: 1.

1 paper.

  1. 2025COFM: Consistent Optimal Transport Flow Matching via Partially Input Convex Neural Networkscited by 0