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 ...

Abstract: Missing values often occur in multivariate time series, affecting data analysis and applications. Existing studies typically use complete data to train imputation models, which are then used ...

Abstract: To address the challenges of traditional marine meteorological prediction methods, which struggle to effectively capture intervariable correlations in multivariate time series data and ...

The final, formatted version of the article will be published soon. Continuous traumatic stress has wide-ranging implications for important life outcomes across multiple domains. We present the design ...