mlsanityData to 7 Oct 2026

kNNSampler: Stochastic Imputations for Recovering Missing Value Distributions

arXiv 2509.08366 ↗First posted 10 Sep 2025stat.ML cs.LG math.STcited by 1

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Abstract (arXiv)

We study a missing-value imputation method, termed kNNSampler, that imputes a given unit's missing response by randomly sampling from the observed responses of the k most similar units to the given unit in terms of the observed covariates. This method can sample unknown missing values from their distributions, quantify the uncertainties of missing values, and be readily used for multiple imputation. Unlike popular kNNImputer, which estimates the conditional mean of a missing response given an observed covariate, kNNSampler is theoretically shown to estimate the conditional distribution of a missing response given an observed covariate. Experiments illustrate the performance of kNNSampler. The code for kNNSampler is made publicly available (https://github.com/SAP/knn-sampler).

Key facts. Cited by 1 paper in the map (data through 7 Oct 2026). Builds on 11 of its 47 references that are in the map. First posted on arXiv 10 Sep 2025.

Builds on

11 of 47 references.

References · 11

  1. 2016Kernel Mean Embedding of Distributions: A Review and Beyondcited by 360
  2. 2018GAIN: Missing Data Imputation using Generative Adversarial Netscited by 349
  3. 2014Matrix Completion and Low-Rank SVD via Fast Alternating Least Squarescited by 104
  4. 2022Optimal Rates for Regularized Conditional Mean Embedding Learningcited by 50
  5. 2020Metrizing Weak Convergence with Maximum Mean Discrepanciescited by 35
  6. 2017Random Forest Missing Data Algorithmscited by 23
  7. 2023Towards Optimal Sobolev Norm Rates for the Vector-Valued Regularized Least-Squares Algorithmcited by 22
  8. 2018Multiple Imputation: A Review of Practical and Theoretical Findingscited by 14
  9. 2024Fast Computation of Leave-One-Out Cross-Validation for k-NN Regressioncited by 4
  10. 2023Numerical Data Imputation for Multimodal Data Sets: A Probabilistic Nearest-Neighbor Kernel Density Approachcited by 3
  11. 2021Imputation Scorescited by 2

Built on by

Cited by year (2026 to 7 Oct)

Citing papers per year: 2026: 1.

1 paper.

  1. 2026Predictive Uncertainty in Short-Term PV Forecasting under Missing Data: A Multiple Imputation Approachcited by 0