GitHub

Code Description for Matrix Sparsity-Based Pauli Decomposition (Python Version)

This document is designed to help users quickly understand, use, and maintain the Python implementation of the Matrix-Sparsity-Based Pauli Decomposition (MSPD) algorithm. It specifies the function, ...
IEEE

Physics-Informed Matrix Factorization Operator

Abstract: Matrix factorization is a fundamental characterization model in machine learning and is usually solved using mathematical decomposition reconstruction loss. However, matrix factorization is ...
Scientific Research Publishing

Devarajan, K. (2008) Nonnegative Matrix Factorization: An Analytical and Interpretive Tool in Computational Biology. PLOS Computational Biology, 4, e1000029.

ABSTRACT: In this paper, an Optimal Predictive Modeling of Nonlinear Transformations “OPMNT” method has been developed while using Orthogonal Nonnegative Matrix Factorization “ONMF” with the ...
Business Wire

Mariner Finance Implements CreditBrowser® from Digital Matrix Systems to Optimize Consumer Dispute Resolution

PLANO, Texas--(BUSINESS WIRE)--Digital Matrix Systems, Inc. (DMS) announced today that Mariner Finance, LLC (“Mariner Finance”) has selected the company’s CreditBrowser® solution. Baltimore-based ...
GitHub

Quantum shannon decomposition fails for QFT with non-unitary matrix error

I encountered an issue when attempting to decompose the unitary matrix of QFT(4) using the built-in quantum_shannon_decomposition function in Cirq. According to the documentation, the ...
IEEE

Enhanced Low-Rank Matrix Decomposition for High-Resolution UAV-SAR Imagery

Abstract: Low-rank matrix decomposition is effective for sparse recovery. However, the conventions are limited in accuracy for high-resolution synthetic aperture radar (SAR) imagery due to the ...