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Tag: multivariate

  • Beyond Uncertainty Sets: Leveraging Optimal Transport to Extend Conformal Predictive Distribution to Multivariate Settings

    Beyond Uncertainty Sets: Leveraging Optimal Transport to Extend Conformal Predictive Distribution to Multivariate Settings arXiv:2511.15146v1 Announce Type: new Abstract: Conformal prediction (CP) constructs uncertainty sets for model outputs with finite-sample coverage guarantees. A candidate output is included in the prediction set if its non-conformity score is not considered extreme relative to the scores observed on…

  • Neural Optimal Transport Meets Multivariate Conformal Prediction

    Neural Optimal Transport Meets Multivariate Conformal Prediction arXiv:2509.25444v1 Announce Type: new Abstract: We propose a framework for conditional vector quantile regression (CVQR) that combines neural optimal transport with amortized optimization, and apply it to multivariate conformal prediction. Classical quantile regression does not extend naturally to multivariate responses, while existing approaches often ignore the geometry of…

  • Wasserstein-Aitchison GAN for angular measures of multivariate extremes

    Wasserstein-Aitchison GAN for angular measures of multivariate extremes arXiv:2504.21438v1 Announce Type: new Abstract: Economically responsible mitigation of multivariate extreme risks — extreme rainfall in a large area, huge variations of many stock prices, widespread breakdowns in transportation systems — requires estimates of the probabilities that such risks will materialize in the future. This paper develops…

  • Online Multivariate Regularized Distributional Regression for High-dimensional Probabilistic Electricity Price Forecasting

    Online Multivariate Regularized Distributional Regression for High-dimensional Probabilistic Electricity Price Forecasting arXiv:2504.02518v1 Announce Type: new Abstract: Probabilistic electricity price forecasting (PEPF) is a key task for market participants in short-term electricity markets. The increasing availability of high-frequency data and the need for real-time decision-making in energy markets require online estimation methods for efficient model updating.…

  • Structured and sparse partial least squares coherence for multivariate cortico-muscular analysis

    Structured and sparse partial least squares coherence for multivariate cortico-muscular analysis arXiv:2503.21802v1 Announce Type: cross Abstract: Multivariate cortico-muscular analysis has recently emerged as a promising approach for evaluating the corticospinal neural pathway. However, current multivariate approaches encounter challenges such as high dimensionality and limited sample sizes, thus restricting their further applications. In this paper, we…

  • Variational Autoencoded Multivariate Spatial Fay-Herriot Models

    Variational Autoencoded Multivariate Spatial Fay-Herriot Models arXiv:2503.14710v1 Announce Type: new Abstract: Small area estimation models are essential for estimating population characteristics in regions with limited sample sizes, thereby supporting policy decisions, demographic studies, and resource allocation, among other use cases. The spatial Fay-Herriot model is one such approach that incorporates spatial dependence to improve estimation…

  • Multivariate Conformal Prediction using Optimal Transport

    Multivariate Conformal Prediction using Optimal Transport arXiv:2502.03609v1 Announce Type: new Abstract: Conformal prediction (CP) quantifies the uncertainty of machine learning models by constructing sets of plausible outputs. These sets are constructed by leveraging a so-called conformity score, a quantity computed using the input point of interest, a prediction model, and past observations. CP sets are…