國立高雄大學圖資館 |

登入

回首頁

Reduction, approximation, machine learning, surrogates, emulators and simulatorsRAMSES /

紀錄類型:	書目-電子資源 : Monograph/item
正題名/作者:	Reduction, approximation, machine learning, surrogates, emulators and simulatorsedited by Gianluigi Rozza ... [et al.].
其他題名:	RAMSES /
其他作者:	Rozza, Gianluigi.
出版者:	Cham :Springer Nature Switzerland :2024.
面頁冊數:	x, 259 p. :ill. (chiefly col.), digital ;24 cm.
Contained By:	Springer Nature eBook
標題:	Approximation theory.
電子資源:	https://doi.org/10.1007/978-3-031-55060-7
ISBN:	9783031550607$q(electronic bk.)

Reduction, approximation, machine learning, surrogates, emulators and simulatorsRAMSES /
Reduction, approximation, machine learning, surrogates, emulators and simulatorsRAMSES /[electronic resource] :edited by Gianluigi Rozza ... [et al.]. - Cham :Springer Nature Switzerland :2024. - x, 259 p. :ill. (chiefly col.), digital ;24 cm. - Lecture notes in computational science and engineering,v. 1512197-7100 ;. - Lecture notes in computational science and engineering ;82..

Shafqat Ali, Francesco Ballarin and Gianluigi Rozza: An online stabilization method for parametrized viscous flows -- Margarita Chasapi, Pablo Antolin, Annalisa Buffa: Reduced order modelling of nonaffine problems on parameterized NURBS multipatch geometries -- Anton Dereventsov, Joseph Daws, Jr., and Clayton G. Webster: Offline Policy Comparison under Limited Historical Agent-Environment Interactions -- Julien Genovese, Francesco Ballarin, Gianluigi Rozza and Claudio Canuto: Weighted reduced order methods for uncertainty quantification in computational fluid dynamics.

This volume is focused on the review of recent algorithmic and mathematical advances and the development of new research directions for Mathematical Model Approximations via RAMSES (Reduced order models, Approximation theory, Machine learning, Surrogates, Emulators, Simulators) in the setting of parametrized partial differential equations also with sparse and noisy data in high-dimensional parameter spaces. The book is a valuable resource for researchers, as well as masters and Ph.D students.

ISBN: 9783031550607$q(electronic bk.)

Standard No.: 10.1007/978-3-031-55060-7doiSubjects--Topical Terms:

185327
Approximation theory.

LC Class. No.: QA221

Dewey Class. No.: 511.4

Reduction, approximation, machine learning, surrogates, emulators and simulatorsRAMSES /
LDR:02204nmm a2200337 a 4500 001 658498
003 DE-He213
005 20240625105822.0
006 m d
007 cr nn 008maaau
008 240923s2024 sz s 0 eng d
020 $a 9783031550607$q(electronic bk.)
020 $a 9783031550591$q(paper)
024 7 $a 10.1007/978-3-031-55060-7 $2 doi
035 $a 978-3-031-55060-7
040 $a GP $c GP
041 0 $a eng
050 4 $a QA221
072 7 $a PBKS $2 bicssc
072 7 $a MAT041000 $2 bisacsh
072 7 $a PBKS $2 thema
082 0 4 $a 511.4 $2 23
090 $a QA221 $b .R321 2024
245 0 0 $a Reduction, approximation, machine learning, surrogates, emulators and simulators $h [electronic resource] : $b RAMSES / $c edited by Gianluigi Rozza ... [et al.].
260 $a Cham : $b Springer Nature Switzerland : $b Imprint: Springer, $c 2024.
300 $a x, 259 p. : $b ill. (chiefly col.), digital ; $c 24 cm.
490 1 $a Lecture notes in computational science and engineering, $x 2197-7100 ; $v v. 151
505 0 $a Shafqat Ali, Francesco Ballarin and Gianluigi Rozza: An online stabilization method for parametrized viscous flows -- Margarita Chasapi, Pablo Antolin, Annalisa Buffa: Reduced order modelling of nonaffine problems on parameterized NURBS multipatch geometries -- Anton Dereventsov, Joseph Daws, Jr., and Clayton G. Webster: Offline Policy Comparison under Limited Historical Agent-Environment Interactions -- Julien Genovese, Francesco Ballarin, Gianluigi Rozza and Claudio Canuto: Weighted reduced order methods for uncertainty quantification in computational fluid dynamics.
520 $a This volume is focused on the review of recent algorithmic and mathematical advances and the development of new research directions for Mathematical Model Approximations via RAMSES (Reduced order models, Approximation theory, Machine learning, Surrogates, Emulators, Simulators) in the setting of parametrized partial differential equations also with sparse and noisy data in high-dimensional parameter spaces. The book is a valuable resource for researchers, as well as masters and Ph.D students.
650 0 $a Approximation theory. $3 185327
650 0 $a Machine learning. $3 188639
650 0 $a Differential equations, Partial. $3 189753
650 0 $a Mathematical models. $3 182479
650 1 4 $a Numerical Analysis. $3 275681
650 2 4 $a Machine Learning. $3 833608
700 1 $a Rozza, Gianluigi. $3 585209
710 2 $a SpringerLink (Online service) $3 273601
773 0 $t Springer Nature eBook
830 0 $a Lecture notes in computational science and engineering ; $v 82. $3 558265
856 4 0 $u https://doi.org/10.1007/978-3-031-55060-7
950 $a Mathematics and Statistics (SpringerNature-11649)