Abstract: With the continuous improvement of power grid stability and reliability requirements, improving the efficiency and accuracy of power system simulation has become an important research topic.

Matrix factorization techniques have become pivotal in data mining, enabling the extraction of latent structures from large-scale data matrices. These methods decompose complex datasets into ...

Abstract: LU-Net is a simple and fast architecture for invertible neural networks (INN) that is based on the factorization of quadratic weight matrices A=LU, where L is a lower triangular matrix with ...

This report investigates solving the system Ax = b through LU decomposition, focusing on both no pivoting and partial pivoting methods applied to symmetric positive definite and randomly generated ...

A comprehensive implementation of various Matrix Decomposition Techniques from the lens of Linear Algebra to produce efficient computing of SVD, PCA, Feature Selection & Data Analysis in Python. To ...