Topological Dynamics in Metamodel Discovery With Artificial - From Biomedical to Cosmological Technologies

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.

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.

Über den Autor / die Autorin

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.

Zusammenfassung

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.

Produktdetails

• Autoren: Ariel Fernandez, Ariel Fernández
• Verlag: Taylor & Francis Ltd.
• Sprache: Englisch
• Produktform: Fester Einband
• Erschienen: 21.12.2022
• EAN: 9781032366326
• ISBN: 978-1-0-3236632-6
• Seiten: 210
• Serie: Chapman & Hall/CRC Artificial Intelligence and Robotics Series
• Themen: Sozialwissenschaften, Recht,Wirtschaft > Medien, Kommunikation > Kommunikationswissenschaft; Artificial Intelligence, MATHEMATICS / Applied, COMPUTERS / Mathematical & Statistical Software, COMPUTERS / Programming / Games, biotechnology, geometry, environmental science, engineering & technology, Biology, life sciences, Topology, Biophysics, Automatic control engineering, Environmental science, engineering and technology, Data analysis: general, Data science and analysis: general