mlsanityData to 7 Oct 2026

Kernel Methods for Causal Functions: Dose, Heterogeneous, and Incremental Response Curves

arXiv 2010.04855 ↗First posted 10 Oct 2020econ.EM cs.LG math.STcited by 36

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Abstract (arXiv)

We propose estimators based on kernel ridge regression for nonparametric causal functions such as dose, heterogeneous, and incremental response curves. Treatment and covariates may be discrete or continuous in general spaces. Due to a decomposition property specific to the RKHS, our estimators have simple closed form solutions. We prove uniform consistency with finite sample rates via original analysis of generalized kernel ridge regression. We extend our main results to counterfactual distributions and to causal functions identified by front and back door criteria. We achieve state-of-the-art performance in nonlinear simulations with many covariates, and conduct a policy evaluation of the US Job Corps training program for disadvantaged youths.

Key facts. Cited by 36 papers in the map (data through 7 Oct 2026). First posted on arXiv 10 Oct 2020.

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Cited by year (2026 to 7 Oct)

Citing papers per year: 2021: 2; 2022: 3; 2023: 5; 2024: 8; 2025: 11; 2026: 7.

36 papers.

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  1. 2023Towards Optimal Sobolev Norm Rates for the Vector-Valued Regularized Least-Squares Algorithmcited by 22
  2. 2023Augmented balancing weights as linear regressioncited by 21
  3. 2022Minimax Optimal Kernel Operator Learning via Multilevel Trainingcited by 13
  4. 2024Optimal Rates for Vector-Valued Spectral Regularization Learning Algorithmscited by 12
  5. 2023An Efficient Doubly-Robust Test for the Kernel Treatment Effectcited by 10
  6. 2025A Dictionary of Closed-Form Kernel Mean Embeddingscited by 9
  7. 2026Dynamics Within Latent Chain-of-Thought: An Empirical Study of Causal Structurecited by 9
  8. 2022A Neural Mean Embedding Approach for Back-door and Front-door Adjustmentcited by 8
  9. 2023Kernel-based off-policy estimation without overlap: Instance optimality beyond semiparametric efficiencycited by 6
  10. 2024Nonparametric Instrumental Variable Regression through Stochastic Approximate Gradientscited by 6
  11. 2025Unveiling and Causalizing CoT: A Causal Pespectivecited by 6
  12. 2021Kernel Ridge Riesz Representers: Generalization, Mis-specification, and the Counterfactual Effective Dimensioncited by 5
24 more
  1. 2021Sequential Kernel Embedding for Mediated and Time-Varying Dose Response Curvescited by 5
  2. 2024An Overview of Causal Inference using Kernel Embeddingscited by 5
  3. 2025Differentially Private Learners for Heterogeneous Treatment Effectscited by 5
  4. 2022Kernel methods for long term dose response curvescited by 4
  5. 2025Kernel-based estimators for functional causal effectscited by 3
  6. 2025Moments of Causal Effectscited by 3
  7. 2025Doubly-Robust Estimation of Counterfactual Policy Mean Embeddingscited by 3
  8. 2024Sources of Gain: Decomposing Performance in Conditional Average Dose Response Estimationcited by 2
  9. 2024Automatic debiasing of neural networks via moment-constrained learningcited by 2
  10. 2024Conditional Outcome Equivalence: A Quantile Alternative to CATEcited by 2
  11. 2024Learning Counterfactual Distributions via Kernel Nearest Neighborscited by 2
  12. 2024Interventional Processes for Causal Uncertainty Quantificationcited by 2
  13. 2025All Models Are Miscalibrated, But Some Less So: Comparing Calibration with Conditional Mean Operatorscited by 2
  14. 2025Density Ratio-Free Doubly Robust Proxy Causal Learningcited by 1
  15. 2025ActiveCQ: Active Estimation of Causal Quantitiescited by 1
  16. 2025Kernel Treatment Effects with Adaptively Collected Datacited by 1
  17. 2025Leveraging semantic similarity for experimentation with AI-generated treatmentscited by 1
  18. 2026Estimating Continuous Treatment Effects with Two-Stage Kernel Ridge Regressioncited by 1
  19. 2023Stable Probability Weighting: Large-Sample and Finite-Sample Estimation and Inference Methods for Heterogeneous Causal Effects of Multivalued Treatments Under Limited Overlapcited by 0
  20. 2026Estimating Aleatoric Uncertainty in the Causal Treatment Effectcited by 0
  21. 2026Optimal and Structure-Adaptive CATE Estimation with Kernel Ridge Regressioncited by 0
  22. 2026Fast Uncertainty Quantification for Kernel-Based Estimators in Large-Scale Causal Inferencecited by 0
  23. 2026Decision-Aware Proximal Bridge Learning for Optimal Treatment Selectioncited by 0
  24. 2026Causal Generalization of Continuous Treatment Effects under Covariate Shiftcited by 0