Abstract: Separable nonlinear least-squares (SNLLS) problems arise frequently in many research fields, such as system identification and machine learning. The variable projection (VP) method is a very ...

Abstract: The identification of separable nonlinear models, prevalent in tasks such as signal analysis, image processing, time series analysis, and machine learning, presents a non-convex optimization ...

This is a preview. Log in through your library . SIAM Journal on Numerical Analysis contains research articles on the development and analysis of numerical methods ...

The influence of discrete boundary conditions on the stability of a finite-difference scheme is difficult to analyze completely. Extraneous eigenvalues may be introduced, and their location is ...

Have physics-informed neural networks been shown to solve partial differential equations whose solutions are non-separable functions? What suitable setups work?: deep/shallow NNs, what type of ...