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Einband grossTopological Dynamics in Metamodel Discovery with Artificial Intelligence
ISBN/GTIN

Topological Dynamics in Metamodel Discovery with Artificial Intelligence

E-BookPDF0 - No protectionE-Book
228 Seiten
Englisch
Taylor & Franciserschienen am21.12.2022
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 multi-scale hierarchies hitherto considered off limits for data science.mehr
Verfügbare Formate
BuchGebunden
EUR113,50
TaschenbuchKartoniert, Paperback
EUR57,00
E-BookPDF0 - No protectionE-Book
EUR60,99
E-BookEPUB0 - No protectionE-Book
EUR60,99

Produkt

KlappentextDealing 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 multi-scale hierarchies hitherto considered off limits for data science.
Details
Weitere ISBN/GTIN9781000806427
ProduktartE-Book
EinbandartE-Book
FormatPDF
Format Hinweis0 - No protection
Erscheinungsjahr2022
Erscheinungsdatum21.12.2022
Seiten228 Seiten
SpracheEnglisch
Dateigrösse33858 Kbytes
Illustrationen73 schwarz-weiße und 16 farbige Abbildungen, 15 schwarz-weiße und 3 farbige Fotos, 58 schwarz-weiße und 13 farbige Zeichnungen
Artikel-Nr.9599424
Rubriken
Genre9200

Inhalt/Kritik

Inhaltsverzeichnis
Preface. About the Author. Part I Fundamentals. Chapter 1 Artificial Intelligence and Dynamical Systems. Chapter 2 Topological Methods for Metamodel Discovery with Artificial Intelligence. Part II Applications. Chapter 3 Artificial Intelligence Reverse-Engineers In Vivo Protein Folding. Chapter 4 The Drug-Induced Protein Folding Problem: Metamodels for Dynamic Targeting. Chapter 5 Targeting Protein Structure in the Absence of Structure: Metamodels for Biomedical Applications. Chapter 6 Autoencoder as Quantum Metamodel of Gravity: Toward an AI-Based Cosmological Technology. Epilogue. Appendix. INDEX.mehr

Autor

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.