collaborators

5 papers

stat.ML2026

Adaptive Multi-Scale Forecasting and Gate-Localized Conformal Prediction for Multivariate Nonstationary Time Series

Ziling Ma, Junshu Jiang, Ángel López-Oriona +2

We propose ABF-T-GLCP, a model-agnostic framework for forecasting and uncertainty quantification in nonstationary multivariate time series. The central idea is to learn an adaptive…

stat.ML2026

Amortized Neural Clustering of Time Series based on Statistical Features

Ángel López-Oriona, Ying Sun

This paper introduces an algorithm-agnostic approach to feature-based time series clustering via amortized neural inference. By training neural networks to approximate the optimal…

stat.AP2025

Robust Spectral Fuzzy Clustering of Multivariate Time Series with Applications to Electroencephalogram

Ziling Ma, Mara Sherlin Talento, Ying Sun +1

Clustering multivariate time series (MTS) is challenging due to non-stationary cross-dependencies, noise contamination, and gradual or overlapping state boundaries. We introduce a…

stat.CO2025

Robust fuzzy clustering for high-dimensional multivariate time series with outlier detection

Ziling Ma, Ángel López-Oriona, Hernando Ombao +1

Fuzzy clustering provides a natural framework for modeling partial memberships, particularly important in multivariate time series (MTS) where state boundaries are often ambiguous.…

stat.ME2025

FCPCA: Fuzzy clustering of high-dimensional time series based on common principal component analysis

Ziling Ma, Ángel López-Oriona, Hernando Ombao +1

Clustering multivariate time series data is a crucial task in many domains, as it enables the identification of meaningful patterns and groups in time-evolving data. Traditional ap…