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Tag: imputation

  • Generative Conditional Missing Imputation Networks

    Generative Conditional Missing Imputation Networks arXiv:2601.00517v1 Announce Type: new Abstract: In this study, we introduce a sophisticated generative conditional strategy designed to impute missing values within datasets, an area of considerable importance in statistical analysis. Specifically, we initially elucidate the theoretical underpinnings of the Generative Conditional Missing Imputation Networks (GCMI), demonstrating its robust properties in…

  • MAGIC: Multi-task Gaussian process for joint imputation and classification in healthcare time series

    MAGIC: Multi-task Gaussian process for joint imputation and classification in healthcare time series arXiv:2509.19577v1 Announce Type: new Abstract: Time series analysis has emerged as an important tool for improving patient diagnosis and management in healthcare applications. However, these applications commonly face two critical challenges: time misalignment and data sparsity. Traditional approaches address these issues through…

  • Imputation-Powered Inference

    Imputation-Powered Inference arXiv:2509.13778v1 Announce Type: cross Abstract: Modern multi-modal and multi-site data frequently suffer from blockwise missingness, where subsets of features are missing for groups of individuals, creating complex patterns that challenge standard inference methods. Existing approaches have critical limitations: complete-case analysis discards informative data and is potentially biased; doubly robust estimators for non-monotone missingness-where…

  • Missing Data Imputation by Reducing Mutual Information with Rectified Flows

    Missing Data Imputation by Reducing Mutual Information with Rectified Flows arXiv:2505.11749v1 Announce Type: new Abstract: This paper introduces a novel iterative method for missing data imputation that sequentially reduces the mutual information between data and their corresponding missing mask. Inspired by GAN-based approaches, which train generators to decrease the predictability of missingness patterns, our method…