Abstract: We present a technique to perform dimensionality reduction on data that is subject to uncertainty. Our method is a generalization of traditional principal component analysis (PCA) to ...

dPCA is a linear dimensionality reduction technique that automatically discovers and highlights the essential features of complex population activities. The population activity is decomposed into a ...

Converts CalculiX ASCII .frd-file to view and postprocess analysis results in Paraview. Generates von Mises and principal components for stress and strain tensors. Creates separate file for each ...

We describe OHBA Software Library for the analysis of electrophysiology data (osl-ephys). This toolbox builds on top of the widely used MNE-Python package and provides unique analysis tools for ...

In the dynamic scene of Python development, understanding the qualification between frameworks and libraries is pivotal for extended success. Python frameworks give structure and support for building ...

Transforming a dataset into one with fewer columns is more complicated than it might seem, explains Dr. James McCaffrey of Microsoft Research in this full-code, step-by-step machine learning tutorial.

Stephen Wallis is a retired nationally recognized school principal and author of the book “Dead Last: The Triumph of Character, Passion, and Teamwork in Education.” Among the most important aspects of ...