Sparse methods are primarily valuable for systems in which the number of non-zero entries is substantially less than the overall size of the matrix. Such situations are common in physical systems, ...

The inspiration for this column comes not from the epic 1999 film The Matrix, as the title may suggest, but from an episode of Sean Carroll’s Mindscape podcast that I listened to over the summer. The ...

In this GEN webinar, our expert speakers will present a case study demonstrating the exceptional properties and high-fidelity performance of ENFINIA Linear DNA.

Abstract: Linear discriminant analysis (LDA) is a widely used technique for data classification. The method offers adequate performance in many classification problems, but it becomes inefficient when ...

LSA-FW is a flexible, modular Python framework for global linear stability analysis of incompressible 2D and 3D flows. It integrates matrix/eigenvalue-based methods, with a strong focus on ...