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Deep learning and computational physics

Record Type:	Electronic resources : Monograph/item
Title/Author:	Deep learning and computational physics/ by Deep Ray, Orazio Pinti, Assad A. Oberai.
Author:	Ray, Deep.
other author:	Pinti, Orazio.
Published:	Cham :Springer Nature Switzerland : : 2024.,
Description:	xvi, 152 p. :ill., digital ;24 cm.
[NT 15003449]:	Introduction -- Introduction to deep neural networks -- Residual neural networks -- Convolutional Neural Networks -- Solving PDEs with Neural Networks -- Operator Networks -- Generative Deep Learning.
Contained By:	Springer Nature eBook
Subject:	Deep learning (Machine learning) -
Online resource:	https://doi.org/10.1007/978-3-031-59345-1
ISBN:	9783031593451

Deep learning and computational physics
Ray, Deep.

Deep learning and computational physics[electronic resource] /by Deep Ray, Orazio Pinti, Assad A. Oberai. - Cham :Springer Nature Switzerland :2024. - xvi, 152 p. :ill., digital ;24 cm.

Introduction -- Introduction to deep neural networks -- Residual neural networks -- Convolutional Neural Networks -- Solving PDEs with Neural Networks -- Operator Networks -- Generative Deep Learning.

The main objective of this book is to introduce a student who is familiar with elementary math concepts to select topics in deep learning. It exploits strong connections between deep learning algorithms and the techniques of computational physics to achieve two important goals. First, it uses concepts from computational physics to develop an understanding of deep learning algorithms. Second, it describes several novel deep learning algorithms for solving challenging problems in computational physics, thereby offering someone who is interested in modeling physical phenomena with a complementary set of tools. It is intended for senior undergraduate and graduate students in science and engineering programs. It is used as a textbook for a course (or a course sequence) for senior-level undergraduate or graduate-level students.

ISBN: 9783031593451

Standard No.: 10.1007/978-3-031-59345-1doiSubjects--Topical Terms:

3538509
Deep learning (Machine learning)

LC Class. No.: Q325.73

Dewey Class. No.: 006.31

Deep learning and computational physics
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100 1 $a Ray, Deep. $3 3719221
245 1 0 $a Deep learning and computational physics $h [electronic resource] / $c by Deep Ray, Orazio Pinti, Assad A. Oberai.
260 $a Cham : $b Springer Nature Switzerland : $b Imprint: Springer, $c 2024.
300 $a xvi, 152 p. : $b ill., digital ; $c 24 cm.
505 0 $a Introduction -- Introduction to deep neural networks -- Residual neural networks -- Convolutional Neural Networks -- Solving PDEs with Neural Networks -- Operator Networks -- Generative Deep Learning.
520 $a The main objective of this book is to introduce a student who is familiar with elementary math concepts to select topics in deep learning. It exploits strong connections between deep learning algorithms and the techniques of computational physics to achieve two important goals. First, it uses concepts from computational physics to develop an understanding of deep learning algorithms. Second, it describes several novel deep learning algorithms for solving challenging problems in computational physics, thereby offering someone who is interested in modeling physical phenomena with a complementary set of tools. It is intended for senior undergraduate and graduate students in science and engineering programs. It is used as a textbook for a course (or a course sequence) for senior-level undergraduate or graduate-level students.
650 0 $a Deep learning (Machine learning) $3 3538509
650 0 $a Computational physics. $3 3343998
650 1 4 $a Data Engineering. $3 3409361
650 2 4 $a Machine Learning. $3 3382522
650 2 4 $a Big Data. $3 3134868
650 2 4 $a Computational Intelligence. $3 1001631
650 2 4 $a Mathematical and Computational Engineering Applications. $3 3592737
650 2 4 $a Theoretical, Mathematical and Computational Physics. $3 1066859
700 1 $a Pinti, Orazio. $3 3719222
700 1 $a Oberai, Assad A. $3 3719223
710 2 $a SpringerLink (Online service) $3 836513
773 0 $t Springer Nature eBook
856 4 0 $u https://doi.org/10.1007/978-3-031-59345-1
950 $a Intelligent Technologies and Robotics (SpringerNature-42732)