IEEE

Reconstructing Network Structures Using Gaussian Mixture Model: From Unsigned to Signed Networks

Abstract: Network reconstruction, which involves inferring a network’s topology from observational data, is a critical challenge in network science. Because observational data are often limited, prior ...
EurekAlert!

Geophysical-machine learning tool for continuous subsurface geomaterials characterization

Researchers utilize 2D electrical resistivity imaging and borehole data to estimate the N60-value of soils with k-means clustering technique Thailand's northern regions, characterized by complex ...
IEEE

Gaussian Mixture Model-Based Soft Consistency for Multi-Task Emotion Recognition

Abstract: The core challenge in multi-task emotion recognition lies in effectively coupling the related tasks of discrete category classification and continuous Valence-Arousal-Dominance (V-A-D) ...
C&EN

Practical Guidance for Training Machine Learning Models in Metabolomics and Mass Spectrometry Research

Department of Chemistry, Faculty of Science, University of British Columbia, Vancouver Campus, 2036 Main Mall, Vancouver, British Columbia V6T 1Z1, Canada Department of Electrical and Computer ...