mlsanityData to 7 Oct 2026

Optimal Transport for Treatment Effect Estimation

arXiv 2310.18286 ↗First posted 27 Oct 2023cs.LG stat.AP stat.MLcited by 32

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Abstract (arXiv)

Estimating conditional average treatment effect from observational data is highly challenging due to the existence of treatment selection bias. Prevalent methods mitigate this issue by aligning distributions of different treatment groups in the latent space. However, there are two critical problems that these methods fail to address: (1) mini-batch sampling effects (MSE), which causes misalignment in non-ideal mini-batches with outcome imbalance and outliers; (2) unobserved confounder effects (UCE), which results in inaccurate discrepancy calculation due to the neglect of unobserved confounders. To tackle these problems, we propose a principled approach named Entire Space CounterFactual Regression (ESCFR), which is a new take on optimal transport in the context of causality. Specifically, based on the framework of stochastic optimal transport, we propose a relaxed mass-preserving regularizer to address the MSE issue and design a proximal factual outcome regularizer to handle the UCE issue. Extensive experiments demonstrate that our proposed ESCFR can successfully tackle the treatment selection bias and achieve significantly better performance than state-of-the-art methods.

Key facts. Cited by 32 papers in the map (data through 7 Oct 2026). Builds on 44 of its 89 references that are in the map. First posted on arXiv 27 Oct 2023.

Builds on

44 of 89 references.

References · 44

  1. 2018Neural Ordinary Differential Equationscited by 3,733
  2. 2013Sinkhorn Distances: Lightspeed Computation of Optimal Transportation Distancescited by 2,277
  3. 2018Computational Optimal Transportcited by 765
  4. 2015Estimation and Inference of Heterogeneous Treatment Effects using Random Forestscited by 597
  5. 2017Meta-learners for Estimating Heterogeneous Treatment Effects using Machine Learningcited by 475
  6. 2015Optimal Transport for Domain Adaptationcited by 457
  7. 2017Quasi-Oracle Estimation of Heterogeneous Treatment Effectscited by 328
  8. 2016Learning Representations for Counterfactual Inferencecited by 327
  9. 2019Adapting Neural Networks for the Estimation of Treatment Effectscited by 285
  10. 2017How to Escape Saddle Points Efficientlycited by 284
  11. 2017Joint Distribution Optimal Transportation for Domain Adaptationcited by 280
  12. 2017Near-linear time approximation algorithms for optimal transport via Sinkhorn iterationcited by 219
32 more
  1. 2021Unbalanced minibatch Optimal Transport; applications to Domain Adaptationcited by 123
  2. 2017Large-Scale Optimal Transport and Mapping Estimationcited by 120
  3. 2018Computational Optimal Transport: Complexity by Accelerated Gradient Descent Is Better Than by Sinkhorn's Algorithmcited by 111
  4. 2016Theoretical Analysis of Domain Adaptation with Optimal Transportcited by 105
  5. 2019Learning Counterfactual Representations for Estimating Individual Dose-Response Curvescited by 90
  6. 2020Generalization Bounds and Representation Learning for Estimation of Potential Outcomes and Causal Effectscited by 72
  7. 2021AutoDebias: Learning to Debias for Recommendationcited by 68
  8. 2020On Unbalanced Optimal Transport: An Analysis of Sinkhorn Algorithmcited by 61
  9. 2019On Efficient Optimal Transport: An Analysis of Greedy and Accelerated Mirror Descent Algorithmscited by 60
  10. 2019Sinkhorn Divergences for Unbalanced Optimal Transportcited by 52
  11. 2022ESCM2: Entire Space Counterfactual Multi-Task Model for Post-Click Conversion Rate Estimationcited by 47
  12. 2018DeepMatch: Balancing Deep Covariate Representations for Causal Inference Using Adversarial Trainingcited by 42
  13. 2019Large-scale Causal Approaches to Debiasing Post-click Conversion Rate Estimation with Multi-task Learningcited by 39
  14. 2021Unbalanced Optimal Transport through Non-negative Penalized Linear Regressioncited by 31
  15. 2022Learning Causal Effects on Hypergraphscited by 31
  16. 2021Enhanced Doubly Robust Learning for Debiasing Post-click Conversion Rate Estimationcited by 28
  17. 2022On the Opportunity of Causal Learning in Recommendation Systems: Foundation, Estimation, Prediction and Challengescited by 28
  18. 2022StableDR: Stabilized Doubly Robust Learning for Recommendation on Data Missing Not at Randomcited by 24
  19. 2022Faster Unbalanced Optimal Transport: Translation invariant Sinkhorn and 1-D Frank-Wolfecited by 22
  20. 2022Optimal transport for causal discoverycited by 19
  21. 2022Learning Disentangled Representations for Counterfactual Regression via Mutual Information Minimizationcited by 18
  22. 2022A Generalized Doubly Robust Learning Framework for Debiasing Post-Click Conversion Rate Predictioncited by 18
  23. 2023Balancing Unobserved Confounding with a Few Unbiased Ratings in Debiased Recommendationscited by 18
  24. 2018Towards Optimal Running Times for Optimal Transportcited by 11
  25. 2022Multiple Robust Learning for Recommendationcited by 11
  26. 2018Improved Techniques for Adversarial Discriminative Domain Adaptationcited by 10
  27. 2020Estimating Causal Effects with the Neural Autoregressive Density Estimatorcited by 8
  28. 2021Copula-based Sensitivity Analysis for Multi-Treatment Causal Inference with Unobserved Confoundingcited by 7
  29. 2021Optimal transport weights for causal inferencecited by 7
  30. 2021Deep Treatment-Adaptive Network for Causal Inferencecited by 5
  31. 2019A Direct tildeO(1/ε) Iteration Parallel Algorithm for Optimal Transportcited by 4
  32. 2023Specify Robust Causal Representation from Mixed Observationscited by 3

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Cited by year (2026 to 7 Oct)

Citing papers per year: 2023: 2; 2024: 10; 2025: 14; 2026: 6.

32 papers.

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  1. 2024FreDF: Learning to Forecast in the Frequency Domaincited by 77
  2. 2024BELM: Bidirectional Explicit Linear Multi-step Sampler for Exact Inversion in Diffusion Modelscited by 29
  3. 2025Time-o1: Time-Series Forecasting Needs Transformed Label Alignmentcited by 22
  4. 2023Bounds on Representation-Induced Confounding Bias for Treatment Effect Estimationcited by 20
  5. 2025DistDF: Time-Series Forecasting Needs Joint-Distribution Wasserstein Alignmentcited by 13
  6. 2024PRANCE: Joint Token-Optimization and Structural Channel-Pruning for Adaptive ViT Inferencecited by 10
  7. 2025Quadratic Direct Forecast for Training Multi-Step Time-Series Forecast Modelscited by 10
  8. 2023GAD-PVI: A General Accelerated Dynamic-Weight Particle-Based Variational Inference Frameworkcited by 9
  9. 2024Debiased Collaborative Filtering with Kernel-Based Causal Balancingcited by 6
  10. 2026CausalRM: Causal-Theoretic Reward Modeling for RLHF from Observational User Feedbackscited by 6
  11. 2024MetaCoCo: A New Few-Shot Classification Benchmark with Spurious Correlationcited by 5
  12. 2024Revisiting Counterfactual Regression through the Lens of Gromov-Wasserstein Information Bottleneckcited by 4
20 more
  1. 2024Rethinking Guidance Information to Utilize Unlabeled Samples:A Label Encoding Perspectivecited by 4
  2. 2024Estimating Long-term Heterogeneous Dose-response Curve: Generalization Bound Leveraging Optimal Transport Weightscited by 4
  3. 2025Orthogonal Representation Learning for Estimating Causal Quantitiescited by 4
  4. 2025Fine-tuning Flow Matching Generative Models with Intermediate Feedbackcited by 4
  5. 2024PairNet: Training with Observed Pairs to Estimate Individual Treatment Effectcited by 3
  6. 2025Enhancing Treatment Effect Estimation via Active Learning: A Counterfactual Covering Perspectivecited by 3
  7. 2026Optimal Transport for LLM Reward Modeling from Noisy Preferencecited by 3
  8. 2024Be Aware of the Neighborhood Effect: Modeling Selection Bias under Interferencecited by 2
  9. 2025Double-Bounded Nonlinear Optimal Transport for Size Constrained Min Cut Clusterincited by 1
  10. 2025Treatment response as a latent variablecited by 1
  11. 2025A Relative Error-Based Evaluation Framework of Heterogeneous Treatment Effect Estimatorscited by 1
  12. 2026Evaluating Uplift Modeling under Structural Biases: Insights into Metric Stability and Model Robustnesscited by 1
  13. 2025Leveraging a Simulator for Learning Causal Representations from Post-Treatment Covariates for CATEcited by 0
  14. 2025Learning Counterfactual Outcomes Under Rank Preservationcited by 0
  15. 2025Minimax Optimal Two-Stage Algorithm For Moment Estimation Under Covariate Shiftcited by 0
  16. 2025Mitigating Hidden Confounding by Progressive Confounder Imputation via Large Language Modelscited by 0
  17. 2025PIPCFR: Pseudo-outcome Imputation with Post-treatment Variables for Individual Treatment Effect Estimationcited by 0
  18. 2026Deep Time-Series Forecasting in 10 Years: A Surveycited by 0
  19. 2026RepFlow: Representation Enhanced Flow Matching for Causal Effect Estimationcited by 0
  20. 2026Treatment Effect Estimation with Differentiated Networked Effect on Graph Datacited by 0