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Applied mathematics and machine learning

Li, Qun - Personal Name; Wood, Aihua - Personal Name;

The simultaneous availability of large datasets and high-performance computing capability in recent years has enabled the rapid development of powerful machine learning algorithms. On the one hand, state-of-the-art machine learning techniques have transformed many areas of science and engineering; on the other hand, theoretical discoveries in mathematical algorithms, differential equations, and statistical inferences, to name a few, have provided the foundation for the exploration of new multidisciplinary models for solving practical problems. This Special Issue endeavors to continue the journey that started in our previous Special Issue (Applied Mathematics and Computational Physics) by providing a platform for researchers from both academia and industry, as well as government, to present their new computational methods that have engineering and physics applications. We publish papers from all areas of mathematics and engineering, and especially those that showcase novel machine learning techniques that leverage subject matter expertise. We aim to foster the communication of the latest research results in the areas of applied and computational mathematics.


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Detail Information
Series Title
-
Call Number
519.8 APP a
Publisher
Basel, Switzerland : MDPI - Multidisciplinary Digital Publishing Institute., 2024
Collation
v, 161 p.: ill.
Language
English
ISBN/ISSN
9783725812820
Classification
519.8
Content Type
-
Media Type
-
Carrier Type
-
Edition
-
Subject(s)
Mathematics
Applied mathematics
Mathematics and Science
Specific Detail Info
-
Statement of Responsibility
-
Other version/related

No other version available

File Attachment
  • 9783725812820
    Other Resource Link
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