Machine Learning Solutions for Inverse Problems: Part A (Hardcover)
Language: English
Published by Elsevier Science Publishing Co Inc, San Diego, 2025
- Hardcover
- New
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Hardcover. Machine Learning Solutions for Inverse Problems: Part A This item is printed on demand. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability.
Seller Inventory # 9780443417894
- Title
- Machine Learning Solutions for Inverse Problems: Part A (Hardcover)
- Author
- Michael Hintermueller
- Publisher
- Elsevier Science Publishing Co Inc, San Diego
- Publication year
- 2025
- Condition
- new
- Binding
- Hardcover
- Language
- English
- ISBN 10
- 044341789X
- ISBN 13
- 9780443417894
Other sections cover Advances in Identifying Differential Equations from Noisy Data Observations, The Complete Electrode Model for Electrical Impedance Tomography: A Comparative Study of Deep Learning and Analytical Methods, Learned Iterative Schemes: Neural Network Architectures for Operator Learning, Jacobian-Free Backpropagation for Unfolded Schemes with Convergence Guarantees, and Operator Learning Meets Inverse Problems: A Probabilistic Perspective
- Provides the authority and expertise of leading contributors from an international board of authors
- Presents the latest release in the Handbook of Numerical Analysis series
- Updated release includes the latest information on the Machine Learning Solutions for Inverse Problems
"Synopsis" may belong to another edition of this title.
About the Author
Bangti Jin received a PhD in Mathematics from The Chinese University
of Hong Kong, Hong Kong in 2008. Previously, he was Lecturer and Reader, and Professor at Department of Computer Science, University
College London (2014-2022), an assistant professor of Mathematics at the University of California, Riverside (2013–2014), a visiting assistant professor at Texas A&M University (2010–2013), an Alexandre von Humboldt Postdoctoral Researcher at University of Bremen (2009–2010). Currently he is Professor of Mathematics, Global STEM Scholar, at The Chinese University of Hong Kong. His research interests include inverse problems, numerical analysis and machine learning.
Carola-Bibiane Schönlieb graduated from the Institute for Mathematics, University of Salzburg (Austria) in 2004. From 2004 to 2005 she held a teaching position in Salzburg. She received her PhD degree from the University of Cambridge (UK) in 2009. After one year of postdoctoral activity at the University of Göttingen (Germany), she became a Lecturer at Cambridge in 2010, promoted to Reader in 2015 and promoted to Professor in 2018. Since 2011 she is a fellow of Jesus College Cambridge. She currently is Professor of Applied Mathematics (2006) at the University of Cambridge where she is head of the Cambridge Image Analysis group. Her current research interests focus on variational methods, partial differential equations and machine learning for image analysis, image processing and inverse imaging problems.
"About the title" may belong to another edition of this title.
CitiRetail
Stevenage, United Kingdom
AbeBooks seller since June 29, 2022
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