Stochastic Methods in Scientific Computing: From Foundations to Advanced Techniques introduces the reader to advanced concepts in stochastic modelling, rooted in an intuitive yet rigorous presentation of the underlying mathematical concepts. A particular emphasis is placed on illuminating the underpinning Mathematics, and yet have the practical applications in mind. The reader will find valuable insights into topics ranging from Social Sciences and Particle Physics to modern-day Computer Science with Machine Learning and AI in focus. The book also covers recent specialised techniques for notorious issues in the field of stochastic simulations, providing a valuable reference for advanced readers with an active interest in the field.

Features

Self-contained, starting from the theoretical foundations and advancing to the most recent developments in the field

Suitable as a reference for post-graduates and researchers or as supplementary reading for courses in numerical methods, scientific computing, and beyond

Interdisciplinary, laying a solid ground for field-specific applications in finance, physics and biosciences on common theoretical foundations

Replete with practical examples of applications to classic and current research problems in various fields.

Authors: Massimo D'Elia, Kurt Langfeld, Biagio Lucini