Dimensionality reduction algorithms

Using the Reduced Basis Method (RBM) to Efficiently Solve Both Differential Equations and Reduce Dimensionality in Scientific Simulations

Feb 11, 2023Esmaeil RezaeiDimensionality reduction algorithms

Introduction to the Reduced Basis (RB) Method The Reduced Basis (RB) Method is a mathematical tool that has been gaining widespread popularity in recent years. It is a model order reduction approach that allows for the efficient yet reliable approximation of input-output relationships induced by parametrized partial differential equations. This method is particularly useful in…

Unleashing the Power of Principal Component Analysis (PCA) for Data Analysis

Principal Component Analysis (PCA) is a widely used statistical method in the field of machine learning, data analysis and pattern recognition. It is a dimensionality reduction technique that helps to simplify complex data sets by transforming them into a new space with reduced dimensions, while preserving most of the important information. In this article, we…