IEEE

A Variable Adaptive Embedding Transformer for Multivariate Time Series Forecasting

Abstract: Multivariate Time Series (MTS) forecasting is crucial in many domains, such as financial market analysis, weather forecasting and energy management. Among various solutions for this task, ...
GitHub

AERCA: Root Cause Analysis of Anomalies in Multivariate Time Series through Granger Causal Discovery (ICLR 2025 Oral)

The AERCA algorithm performs robust root cause analysis in multivariate time series data by leveraging Granger causal discovery methods. This implementation in PyTorch facilitates experimentation on ...
IEEE

Multivariate Variable-Step Multiscale Extended Dispersion Entropy-Based Lempel–Ziv Complexity and Its Application in Fault Diagnosis

Abstract: Extended dispersion entropy-based Lempel–Ziv complexity (EDELZC) can measure the irregularity or chaos of single-channel time series, which is one of the ideal tools for extracting fault ...
GitHub

Model-Based Clustering and Variable Selection for Multivariate Count Data

Model-based clustering provides a principled way of developing clustering methods. We develop a new model-based clustering methods for count data. The method combines clustering and variable selection ...