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New method for multivariate time series prediction sets unveiled

By PulseAugur Editorial · [2 sources] ·

Researchers have introduced filtered conformal ellipsoids, a novel method for joint prediction sets in multivariate time series. This approach utilizes a state-space filter to emit predictive means and covariances, which are then calibrated using split-conformal methods. The framework aims to control single events while adapting to cross-coordinate dependencies, benefiting from learned predictive covariances without relying on Gaussian tail probabilities for coverage. AI

IMPACT Introduces a new framework for multivariate time series prediction, potentially improving accuracy in complex sequential data analysis.

RANK_REASON The cluster contains a research paper published on arXiv detailing a new method for time series analysis.

Read on arXiv cs.LG →

AI-generated summary · Google Gemini · from 2 sources. How we write summaries →

New method for multivariate time series prediction sets unveiled

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The cluster contains a research paper published on arXiv detailing a new method for time series analysis.
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COVERAGE [2]

  1. arXiv cs.LG TIER_1 English(EN) · Yannick Limmer ·

    Filtered Conformal Ellipsoids for Graph-Native Time Series

    arXiv:2606.17014v1 Announce Type: new Abstract: Joint prediction sets for multivariate time series should control a single event while adapting to cross-coordinate dependence. We study filtered conformal ellipsoids: a frozen state-space filter emits a one-step predictive mean and…

  2. arXiv stat.ML TIER_1 English(EN) · Yannick Limmer ·

    Filtered Conformal Ellipsoids for Graph-Native Time Series

    Joint prediction sets for multivariate time series should control a single event while adapting to cross-coordinate dependence. We study filtered conformal ellipsoids: a frozen state-space filter emits a one-step predictive mean and covariance, and split-conformal calibration is …

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