Introduces MO-ARM framework for training order-agnostic autoregressive models directly on incomplete data, showing implicit MCAR imputation in standard training and outperforming baselines on benchmarks.
Miwae: Deep generative modelling and imputation of incomplete data sets
2 Pith papers cite this work. Polarity classification is still indexing.
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Pith papers citing it
years
2026 2verdicts
UNVERDICTED 2representative citing papers
DRIO adds worst-case Wasserstein regularization to time series imputation, yielding a tractable adversarial surrogate and alternating algorithm that improves robustness under missingness.
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Order-Agnostic Autoregressive Modelling with Missing Data
Introduces MO-ARM framework for training order-agnostic autoregressive models directly on incomplete data, showing implicit MCAR imputation in standard training and outperforming baselines on benchmarks.
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Multivariate Time Series Data Imputation via Distributionally Robust Regularization
DRIO adds worst-case Wasserstein regularization to time series imputation, yielding a tractable adversarial surrogate and alternating algorithm that improves robustness under missingness.