Clinical and Surgical Aspects of Congenital Heart Diseases (1版)

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This text and guide discusses the surgical and medical management of congenital heart diseases in both adult and children. It describes the disease, pathology, treatment, complications and follow-up with extensive use of didactic material to educate the reader to the practicalities of the subject. It details the novel research via an extensive literature review, while covering all aspects of the surgical and medical treatment of congenital heart disease. It includes review of the laparoscopic techniques and epidemiology of each disease involved and their prevalence to provide the reader with the full clinical picture. Clinical and Surgical Aspects of Congenital Heart Diseases: Text and Study Guide provides a thorough practical reference for the discipline with the use of illustrations and charts to facilitate understanding. It is essential reading for all trainee and practicing cardiac surgeons, cardiologists and internists, and all interested healthcare professionals.

Modern Aspects of Dynamical Systems: Cetraro, Italy 2021 (1版)

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【簡介】 This book provides an overview of recent advances in the theory of dynamical systems, with a particular emphasis on their connections to other areas of mathematical research, including number theory, geometry, mathematical physics, complex analysis, and celestial mechanics. Compiling the lecture notes from some of the contributions presented at the C.I.M.E. school "Modern Aspects of Dynamical Systems" held in Cetraro in August 2021, the contributions are the following: “Homogeneous dynamics and Diophantine problems” by Manfred Einsiedler, “Effective ergodic theory for translation flow” by Giovanni Forni, “Integrability and rigidity for convex billiards” by Vadim Kaloshin, “Holomorphic dynamics” by Jasmin Raissy and “Exponentially small phenomena and its role in the dynamics” by Tere Martinez-Seara. These notes are suitable for graduate students and young researchers interested in an introduction to some of the modern research areas within the field of dynamical systems. 【目錄】

Mathematical Aspects of Deep Learning

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In recent years the development of new classification and regression algorithms based on deep learning has led to a revolution in the fields of artificial intelligence, machine learning, and data analysis. The development of a theoretical foundation to guarantee the success of these algorithms constitutes one of the most active and exciting research topics in applied mathematics. This book presents the current mathematical understanding of deep learning methods from the point of view of the leading experts in the field. It serves both as a starting point for researchers and graduate students in computer science, mathematics, and statistics trying to get into the field and as an invaluable reference for future research. Written by a group of leading experts in the field Presents deep learning methods from a mathematical, rather than a computer science, perspective Covers topics including generalization in deep learning, expressivity of deep neural networks, sparsity enforcing algorithms, and the scattering transform