About this book series
SpringerBriefs on PDEs and Data Science targets contributions that will impact the understanding of partial differential equations (PDEs), and the emerging research of the mathematical treatment of data science.
The series will accept high-quality original research and survey manuscripts covering a broad range of topics including analytical methods for PDEs, numerical and algorithmic developments, control, optimization, calculus of variations, optimal design, data driven modelling, and machine learning. Submissions addressing relevant contemporary applications such as industrial processes, signal and image processing, mathematical biology, materials science, and computer vision will also be considered.
The series is the continuation of a former editorial cooperation with BCAM, which resulted in the publication of 28 titles as listed here: https://www.springer.com/gp/mathematics/bcam-springerbriefs
- Electronic ISSN
- 2731-7609
- Print ISSN
- 2731-7595
- Editor-in-Chief
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- Enrique Zuazua
- Series Editor
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- Irene Fonseca,
- Franca Hoffmann,
- Shi Jin,
- Juan J. Manfredi,
- Emmanuel Trélat,
- Xu Zhang
