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Scalable Optimal Transport

A curated list of research works and resources on optimal transport in machine learning. Related Paper.

@article{khamis24OT,
      title={Scalable Optimal Transport Methods in Machine Learning: A Contemporary Survey}, 
      author={Abdelwahed Khamis and Russell Tsuchida and Mohamed Tarek and Vivien Rolland and Lars Petersson},
      year={2024},
      journal={IEEE Transactions on Pattern Analysis and Machine Intelligence},
      publisher={IEEE}
}

Contents

Sections:

Background

2021 - SIAM Stochastic control liaisons: Richard sinkhorn meets gaspard monge on a schrodinger bridge
2019 - Computational optimal transport: With applications to data science
2015 - Optimal transport for applied mathematicians: calculus of variations, PDEs, and modeling
2009 - Optimal transport: old and new
2093 - Topics in optimal transportation
2006 - On a problem of monge

Regularized OT

2023 - CoRL Watch and match: Supercharging imitation with regularized optimal transport Code
2022 - IG Entropy-regularized 2-wasserstein distance between gaussian measures
2021 - ICDM A regularized wasserstein framework for graph kernels
2020 - TMLR MMD-regularized Unbalanced Optimal Transport Code
2020 - ICML Regularized optimal transport is ground cost adversarial
2020 - SIAM Empirical regularized optimal transport: Statistical theory and applications
2019 - Quantum entropic regularization of matrix-valued optimal transport
2019 - SIAM Stabilized sparse scaling algorithms for entropy regularized transport problems
2018 - SIAM Semidual regularized optimal transport
2018 - AISTATS Smooth and sparse optimal transport
2014 - NeurIPS Optimal transport with laplacian regularization
2014 - SIAM Regularized discrete optimal transport Code

Sinkhorn

2022 - CVPR A unified framework for implicit sinkhorn differentiation
2021 - ICML Low-rank sinkhorn factorization
2021 - A note on overrelaxation in the sinkhorn algorithm
2020 - NeurIPS Faster wasserstein distance estimation with the sinkhorn divergence Code
2020 - ICML On unbalanced optimal transport: An analysis of sinkhorn algorithm Code
2020 - NeurIPS Linear time sinkhorn divergences using positive features
2019 - NeurIPS Massively scalable sinkhorn distances via the nyström method
2019 - AISTATS Interpolating between optimal transport and mmd using sinkhorn divergences
2019 - arXiv Sinkhorn divergences for unbalanced optimal transport
2019 - AISTATS Sample complexity of sinkhorn divergences
2019 - ICML Wasserstein adversarial examples via projected sinkhorn iterations
2019 - NeurIPS Differentiable Ranking and Sorting using Optimal Transport
2018 - ICML Computational optimal transport: Complexity by accelerated gradient descent is better than by sinkhorn’s algorithm
2018 - ICLR Learning latent permutations with gumbel-sinkhorn networks Code
2017 - NeurIPS Overrelaxed sinkhorn-knopp algorithm for regularized optimal transport
2013 - NeurIPS Sinkhorn Distances: Lightspeed Computation of Optimal Transport Code
2011 - Ranking via sinkhorn propagation
2008 - SIAM The sinkhorn–knopp algorithm: convergence and applications

Unbalanced and Partial OT

2022 - arXiv Unbalanced optimal transport, from theory to numerics
2021 - ICPR Unbalanced optimal transport in multi-camera tracking applications
2021 - AAAI Learning to count via unbalanced optimal transport
2020 - NeurIPS Partial optimal tranport with applications on positive-unlabeled learning
2020 - NeurIPS Entropic optimal transport between unbalanced gaussian measures has a closed form
2018 - Unbalanced optimal transport: Dynamic and kantorovich formulations

Structured OT

2024 - ICML Submodular Framework for Structured-Sparse Optimal Transport Code
2023 - ICLR Sparsity-Constrained Optimal Transport
2019 - NeurIPS Hierarchical optimal transport for document representation Code
2018 - AISTATS Structured optimal transport

Dynamic OT & Schrodinger Bridge

2023 - arXiv Transport with support: Data-conditional diffusion bridges

Multi-Marginal & Wasserstein Barycenter

2021 - SIAM Multimarginal optimal transport with a tree-structured cost and the schrodinger bridge problem
2020 - ICML Debiased sinkhorn barycenters
2020 - NeurIPS Continuous regularized wasserstein barycenters Code
2020 - Multi-marginal optimal transport using partial information with applications in robust localization and sensor fusion
2016 - ACM ToG Wasserstein barycentric coordinates: Histogram regression using optimal transport
2015 - Sliced and radon wasserstein barycenters of measures Code
2011 - SIAM Barycenters in the wasserstein space

Tree Wasserstein

2023 - TMLR Approximating 1-wasserstein distance with trees
2022 - AISTATS Fixed support tree-sliced wasserstein barycenter Code
2021 - ICML Supervised tree-wasserstein distance
2020 - NeurIPS Fast unbalanced optimal transport on a tree Code
2019 - NeurIPS Tree-sliced variants of wasserstein distances Code

Gromov Wasserstein

2022 - A brief survey on computational gromov-wasserstein distance
2022 - arXiv Gromov-wasserstein autoencoders Code
2022 - ICML Entropic gromov-wasserstein between gaussian distributions
2021 - AISTATS Aligning time series on incomparable spaces
2021 - ECML PKDD Quantized gromov-wasserstein Code
2020 - ICML Gromov-Wasserstein Optimal Transport to Align Single-Cell Multi-Omics Data
2020 - A contribution to optimal transport on incomparable spaces
2019 - NeurIPS Asymptotic guarantees for learning generative models with the sliced-wasserstein distance
2019 - CVPR Max-sliced wasserstein distance and its use for gans
2018 - EMNLP Gromov-wasserstein alignment of word embedding spaces Code
2016 - ICML Gromov-wasserstein averaging of kernel and distance matrices Code
2011 - Gromov–wasserstein distances and the metric approach to object matching

Sliced Wasserstein

2021 - NeurIPS Pooling by sliced-wasserstein embedding Code
2021 - CVPR A sliced wasserstein loss for neural texture synthesis Code
2021 - ICML Differentially private sliced wasserstein distance
2020 - NeurIPS Statistical and topological properties of sliced probability divergences
2019 - NeurIPS Sliced gromov-wasserstein Code
2019 - NeurIPS Generalized sliced wasserstein distances
2016 - CVPR Sliced wasserstein kernels for probability distributions

Other formulations

2023 - ECML PKDD Feature-robust optimal transport for high-dimensional data
2022 - ICML Order constraints in optimal transport Code
2021 - ICML Outlier-robust optimal transport
2020 - AISTATS Unsupervised hierarchy matching with optimal transport over hyperbolic spaces
2020 - ICML A swiss army knife for minimax optimal transport Code
2020 - NeurIPS Co-optimal transport Code
2017 - CVPR Order-preserving wasserstein distance for sequence matching

Theoretical and Complexity

2022 - Estimation of wasserstein distances in the spiked transport model
2022 - NeurIPS Asymptotics of smoothed wasserstein distances in the small noise regime
2021 - NeurIPS Rates of estimation of optimal transport maps using plug-in estimators via barycentric projections
2021 - arXiv Plugin estimation of smooth optimal transport maps
2021 - arXiv A short proof on the rate of convergence of the empirical measure for the wasserstein distance
2021 - NeurIPS Averaging on the bures-wasserstein manifold: dimension-free convergence of gradient descent
2021 - NeurIPS Dimensionality reduction for wasserstein barycenter
2020 - Convergence and concentration of empirical measures under wasserstein distance in unbounded functional spaces
2020 - arXiv A study of performance of optimal transport Code
2020 - arXiv The statistical effect of entropic regularization in optimal transportation
2019 - Sharp asymptotic and finite-sample rates of convergence of empirical measures in wasserstein distance
2019 - arXiv Strong equivalence between metrics of wasserstein type
2018 - Optimal entropy-transport problems and a new hellinger–kantorovich distance between positive measures
2016 - SIAM A smoothed dual approach for variational wasserstein problems Code

Scaling OT

Measures simplification

2022 - AMTA Quantized wasserstein procrustes alignment of word embedding spaces
2022 - WIRE CS Projection-based techniques for high-dimensional optimal transport problems
2021 - UAI Improving approximate optimal transport distances using quantization
2021 - MDPI-ASubspace detours meet gromov–wasserstein
2021 - ICML Projection robust wasserstein barycenters
2020 - AISTATS Gaussian-smoothed optimal transport: Metric structure and statistical efficiency
2019 - ICML Subspace robust wasserstein distances Code
2019 - NeurIPS Subspace detours: Building transport plans that are optimal on subspace projections
2019 - NeurIPS Large-scale optimal transport map estimation using projection pursuit Code

Cost and Kernel Approximation

2021 - ICML Scalable optimal transport in high dimensions for graph distances, embedding alignment, and more Code
2019 - SIAM Stabilized sparse scaling algorithms for entropy regularized transport problems

Plan Structuring

2022 - NeurIPS Low-rank optimal transport: Approximation, statistics and debiasing
2022 - ICML Linear-time gromov wasserstein distances using low rank couplings and costs
2021 - arXiv Approximating optimal transport via low-rank and sparse factorization
2021 - Making transport more robust and interpretable by moving data through a small number of anchor points
2019 - AISTATS Statistical optimal transport via factored couplings

Computation Partitioning

2022 - arXiv Budget-constrained bounds for mini-batch estimation of optimal transport
2022 - CVPR Computing wasserstein-p distance between images with linear cost
2021 - Deep learning and optimal transport: learning from one another
2020 - arXiv Mrec: a fast and versatile framework for aligning and matching point clouds with applications to single cell molecular data
2020 - AISTATS Learning with minibatch wasserstein: asymptotic and gradient properties Code
2019 - JMLR Optimal transport: Fast probabilistic approximation with exact solvers.
2019 - NeurIPS Scalable gromov-wasserstein learning for graph partitioning and matching Code
2017 - JMLR Multiscale strategies for computing optimal transport Code
2011 - CGF A multiscale approach to optimal transport

Solver Acceleration

2023 - AISTATS Rethinking initialization of the sinkhorn algorithm
2022 - JMIV Learning to generate wasserstein barycenters Code
2022 - NeurIPS Supervised training of conditional monge maps
2022 - NeurIPS Wasserstein iterative networks for barycenter estimation Code
2022 - Kantorovich strikes back! wasserstein gans are not optimal transport?
2022 - AAAI Efficient optimal transport algorithm by accelerated gradient descent
2022 - AAAI Exploiting problem structure in deep declarative networks: Two case studies
2022 - arXiv Meta optimal transport Code
2021 - arXiv Wasserstein gans work because they fail (to approximate the wasserstein distance)
2021 - ICML Scalable computations of wasserstein barycenter via input convex neural networks
2021 - NeurIPS Do neural optimal transport solvers work? a continuous wasserstein-2 benchmark
2020 - ECAI Speeding up word mover’s distance and its variants via properties of distances between embeddings
2020 - UAI A fast proximal point method for computing exact wasserstein distance
2020 - ICML Optimal transport mapping via input convex neural networks
2018 - ICLR Large-scale optimal transport and mapping estimation Code
2017 - Linear-complexity relaxed word mover's distance with gpu acceleration
2016 - NeurIPS Stochastic optimization for large-scale optimal transport Code

Applications

Generative Models

2022 - NeurIPS Score-based Generative Modeling Secretly Minimizes the Wasserstein Distance Code
2021 - NeurIPS Maximum likelihood training of score-based diffusion models Code
2021 - NeurIPS Diffusion schrödinger bridge with applications to score-based generative modeling
2021 - ICLR Distributional sliced-wasserstein and applications to generative modeling
2021 - AAAI Towards generalized implementation of wasserstein distance in gans
2020 - NeurIPS Asymptotic guarantees for generative modeling based on the smooth wasserstein distance
2020 - ICLR Wasserstein-2 generative networks Code
2019 - ICML Learning generative models across incomparable spaces Code
2018 - AISTATS Learning generative models with sinkhorn divergences
2017 - ICML Wasserstein generative adversarial networks Code
2017 - From optimal transport to generative modeling: the vegan cookbook
2017 - NeurIPS Improved training of wasserstein gans Code

Domain Adaptation

2022 - ML Hierarchical optimal transport for unsupervised domain adaptation Code
2022 - ICLR Cross-domain imitation learning via optimal transport Code
2022 - IEEE TIP Few-shot domain adaptation via mixup optimal transport
2021 - ICML Unbalanced minibatch optimal transport; applications to domain adaptation Code
2021 - CVPR Wasserstein contrastive representation distillation
2021 - NeurIPS Lifelong domain adaptation via consolidated internal distribution
2021 - CVPR OTCE: A transferability metric for cross-domain cross-task representations Code
2021 - ICCV The right to talk: An audio-visual transformer approach Code
2021 - WACV Zero-shot recognition via optimal transport
2020 - CVPR Deepemd: Few-shot image classification with differentiable earth mover's distance and structured classifiers Code
2020 - ICML Margin-aware adversarial domain adaptation with optimal transport Code
2020 - ECCV Learning to generate novel domains for domain generalization Code
2020 - IJCAI Joint partial optimal transport for open set domain adaptation.
2020 - BMVC Weakly supervised cross-domain alignment with optimal transport
2020 - ICCV Transporting labels via hierarchical optimal transport for semi-supervised learning
2020 - NeurIPS Geometric dataset distances via optimal transport Code
2019 - CVPR Sliced wasserstein discrepancy for unsupervised domain adaptation Code
2019 - AISTATS Optimal transport for multi-source domain adaptation under target shift Code
2019 - NeurIPS Hierarchical optimal transport for multimodal distribution alignment
2018 - AAAI Wasserstein distance guided representation learning for domain adaptation
2018 - ICCV Deepjdot: Deep joint distribution optimal transport for unsupervised domain adaptation
2017 - ECML PKDD Theoretical analysis of domain adaptation with optimal transport
2017 - NeurIPS Joint distribution optimal transportation for domain adaptation Code
2016 - TPAMI Optimal transport for domain adaptation Code

Other Applications

2022 - CVPR Motion-modulated temporal fragment alignment network for few-shot action recognition Action Recognition
2022 - AISTATS Sinkformers: Transformers with doubly stochastic attention Transformers
2022 - AISTATS Proximal optimal transport modeling of population dynamics Code Modeling Dynamics
2022 - NeurIPS Optimal transport of classifiers to fairness Code Fairness in ML
2022 - CVPR Unsupervised action segmentation by joint representation learning and online clustering Action Segmentation
2021 - CVPR Ota: Optimal transport assignment for object detection Code Object Detection
2021 - ICCV Point-set distances for learning representations of 3d point clouds Code Point Cloud
2021 - CVPR A generalized loss function for crowd counting and localization Code Crowd Counting
2021 - WACV Augmented self-labeling for source-free unsupervised domain adaptation Self Labelling
2021 - NeurIPS Measuring generalization with optimal transport Code Generalization in ML
2021 - ICLR Convex potential flows: Universal probability distributions with optimal transport and convex optimization Normalizing Flow
2020 - NeurIPS Model fusion via optimal transport Code Model Fusion
2020 - ECCV Solving the blind perspective-n-point problem end-to-end with robust differentiable geometric optimization Code PnP problem
2019 - ICLR Self-labelling via simultaneous clustering and representation learning Code Self Labelling
2019 - ICML Obtaining fairness using optimal transport theory Code Fairness in ML
2019 - ICLR Learning embeddings into entropic wasserstein spaces Code Embedding
2015 - ICML From word embeddings to document distances Code Document Matching
2018 - TPAMI Visual permutation learning Code Permutation Learning
Correspondance & Matching:
- 2021 - CVPR Loftr: Detector-free local feature matching with transformers Code
- 2020 - CVPR Superglue: Learning feature matching with graph neural networks Code
- 2020 - arXiv Learning 3d-3d correspondences for one-shot partial-to-partial registration
Graphs:
- 2022 - ICML Learning to predict graphs with fused gromov-wasserstein barycenters
- 2020 - NeurIPS Copt: Coordinated optimal transport on graphs Code
- 2020 - ICLR Deep graph matching consensus Code
- 2019 - ICML Optimal transport for structured data with application on graphs Code
- 2019 - ICML Gromov-wasserstein learning for graph matching and node embedding Code

Software and Tools

2022 - arXiv Optimal transport tools (ott): A jax toolbox for all things wasserstein Code
2021 - JMLR Pot: Python optimal transport Code
2020 - NeurIPS Fast geometric learning with symbolic matrices Code

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Optimal Transport in the Big Data Era

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