Abstract: We present a novel visual representation and interface named the matrix of isosurface similarity maps (MISM) for effective exploration of large time-varying multivariate volumetric data sets ...

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: The study of taxation is essential to understanding the processes that encourage or hinder revenue collection. In Mexico and other federal countries, subnational governments may levy certain ...

Matrix factorization techniques, such as principal component analysis (PCA) and independent component analysis (ICA), are widely used to extract geological processes from geochemical data. However, ...

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Department of Sustainable Development and Ecological Transition, Università del Piemonte Orientale, Piazza Sant’Eusebio 5, Vercelli 13100, Italy ...

Abstract: This study presents a relaxation method for second-order matrix-valued multivariate polynomial inequalities(SMMPI), with a specific application to the ...