activity
20212026
collaborators

7 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.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…

stat.ME2024

Dependence-based fuzzy clustering of functional time series

Angel Lopez-Oriona, Ying Sun, Han Lin Shang

Time series clustering is essential in scientific applications, yet methods for functional time series, collections of infinite-dimensional curves treated as random elements in a H…

stat.AP2024

Fuzzy clustering of circular time series based on a new dependence measure with applications to wind data

Ángel López-Oriona, Ying Sun, Rosa M. Crujeiras

Time series clustering is an essential machine learning task with applications in many disciplines. While the majority of the methods focus on time series taking values on the real…

stat.ME2021

Quantile-based fuzzy C-means clustering of multivariate time series: Robust techniques

Ángel López-Oriona, Pierpaolo D'Urso, José Antonio Vilar +1

Three robust methods for clustering multivariate time series from the point of view of generating processes are proposed. The procedures are robust versions of a fuzzy C-means mode…