Aims & Scope
Analysis and Applications publishes high quality mathematical papers that treat those parts of analysis which have direct or potential applications to the physical, biological, computer and data sciences and engineering. Some of the topics from analysis include approximation theory, asymptotic analysis, calculus of variations, deep neural networks, integral equations, integral transforms, machine learning, optimization, ordinary and partial differential equations, perturbation methods, and statistical learning theory. The primary aim of the journal is to encourage the development of new techniques and results in applied analysis.