Topological Dynamics in Metamodel Discovery with Artificial Intelligence: From Biomedical to Cosmological Technologies
暫譯: 人工智慧在元模型發現中的拓撲動力學：從生物醫學到宇宙技術
Fernández, Ariel
相關主題
商品描述
The leveraging of artificial intelligence (AI) for model discovery in dynamical systems is cross-fertilizing and revolutionizing both disciplines, heralding a new era of data-driven science. This book is placed at the forefront of this endeavor, taking model discovery to the next level.
Dealing with artificial intelligence, this book delineates AI's role in model discovery for dynamical systems. With the implementation of topological methods to construct metamodels, it engages with levels of complexity and multiscale hierarchies hitherto considered off limits for data science.
Key Features:
- Introduces new and advanced methods of model discovery for time series data using artificial intelligence
- Implements topological approaches to distill machine-intuitive models from complex dynamics data
- Introduces a new paradigm for a parsimonious model of a dynamical system without resorting to differential equations
- Heralds a new era in data-driven science and engineering based on the operational concept of computational intuition
Intended for graduate students, researchers, and practitioners interested in dynamical systems empowered by AI or machine learning and in their biological, engineering, and biomedical applications, this book will represent a significant educational resource for people engaged in AI-related cross-disciplinary projects.
商品描述(中文翻譯)
利用人工智慧（AI）進行動態系統的模型發現正在交叉促進並革新這兩個領域，預示著數據驅動科學的新時代。本書位於這一努力的最前沿，將模型發現提升到新的層次。
本書探討人工智慧在動態系統模型發現中的角色。通過實施拓撲方法來構建元模型，它涉及到以往被認為是數據科學禁區的複雜性和多尺度層次。
**主要特點：**
- 介紹使用人工智慧進行時間序列數據模型發現的新方法和先進方法
- 實施拓撲方法，從複雜動態數據中提煉出機器直觀模型
- 引入一種新的範式，為動態系統提供簡約模型，而無需依賴微分方程
- 預示基於計算直覺操作概念的數據驅動科學和工程的新時代
本書旨在為研究生、研究人員和實踐者提供資源，特別是對於那些對由AI或機器學習驅動的動態系統及其在生物、工程和生醫應用中的應用感興趣的人士，將成為參與AI相關跨學科項目的重要教育資源。
作者簡介
Ariel Fernández is an Argentine-American physical chemist and mathematician. He obtained a Ph. D. degree in Chemical Physics from Yale University and held the Hasselmann Endowed Chair Professorship in Bioengineering at Rice University until his retirement. To date, he has published over 400 scientific papers in professional journals including PNAS, Nature, Nature Biotechnology, Physical Review Letters, Genome Research and Genome Biology. Fernández has also authored five books on biophysics and molecular medicine and holds several patents on technological innovation. Since 2018 Fernández heads the Daruma Institute for Applied Intelligence, the research arm of AF Innovation, a Consultancy based in Argentina and the USA.
作者簡介(中文翻譯)
阿里爾·費爾南德茲（Ariel Fernández）是一位阿根廷裔美國物理化學家和數學家。他在耶魯大學獲得化學物理博士學位，並在萊斯大學擔任哈塞爾曼（Hasselmann）生物工程講座教授，直到退休為止。至今，他已在專業期刊上發表超過400篇科學論文，包括《美國國家科學院院刊》（PNAS）、《自然》（Nature）、《自然生物技術》（Nature Biotechnology）、《物理評論快報》（Physical Review Letters）、《基因組研究》（Genome Research）和《基因組生物學》（Genome Biology）。費爾南德茲還撰寫了五本有關生物物理學和分子醫學的書籍，並擁有多項技術創新專利。自2018年以來，費爾南德茲擔任達魯瑪應用智慧研究所（Daruma Institute for Applied Intelligence）的負責人，該研究所是AF Innovation的研究部門，AF Innovation是一家總部位於阿根廷和美國的顧問公司。
