Generative AI can augment chemometrics by automating curation, connecting analytical outputs to textual knowledge, and ...

In his doctoral thesis, Michael Roop develops numerical methods that allow finding physically reliable approximate solutions ...

Visualization, Dimensionality Reduction, Reproducibility, Stability, Multivariate Quantum Data, Information Retrieval ...

Managing irregular multivariate time series (IMTS) data is a significant challenge due to inherent irregularities and missing values. Recent advancements have utilized graph neural networks (GNNs) to ...

Genome-Wide Association Studies (GWAS) have transformed human genetics by identifying thousands of loci associated with complex traits and diseases. Yet, individual GWAS are often underpowered, and ...

Welcome to the 14th Cochrane Methods report compiled by the Central Executive Team to provide an overview of the key methodological activities in Cochrane for 2024–2025. The report highlights the ...

The biopharmaceutical industry must navigate a complex ecosystem in which therapy innovation is linked intrinsically to stringent quality standards and regulatory mandates. Raman spectroscopy has ...

Creative Commons (CC): This is a Creative Commons license. Attribution (BY): Credit must be given to the creator. The extensive diversity of tea, resulting from varietal traits and manufacturing ...

Abstract: Clustering multivariate time-series data is crucial for uncovering complex temporal patterns in dynamic environments, such as building indoor conditions and behavior where variables like ...

Abstract: This article introduces a novel extension of the multivariate variational mode decomposition (MVMD) method, termed fuzzy MVMD (FMVMD), designed to enhance alignment information extraction.