LEADER 02318nam0 2200505 i 450 001 VAN0123409 005 20230704120758.185 017 70$2N$a9783319543390 100 $a20190919d2017 |0itac50 ba 101 $aeng 102 $aCH 105 $a|||| ||||| 200 1 $aUncertainty quantification$ean accelerated course with advanced applications in computational engineering$fChristian Soize 210 $aCham$cSpringer$d2017 215 $axxii, 329 p.$cill.$d24 cm 410 1$1001VAN0044474$12001 $aInterdisciplinary applied mathematics$1210 $aNew York [etc.]$cSpringer$v47 500 1$3VAN0235973$aUncertainty quantification$91560479 606 $a47-XX$xOperator theory [MSC 2020]$3VANC019759$2MF 606 $a35-XX$xPartial differential equations [MSC 2020]$3VANC019763$2MF 606 $a37-XX$xDynamical systems and ergodic theory [MSC 2020]$3VANC020363$2MF 606 $a60-XX$xProbability theory and stochastic processes [MSC 2020]$3VANC020428$2MF 606 $a15-XX$xLinear and multilinear algebra; matrix theory [MSC 2020]$3VANC020607$2MF 606 $a62-XX$xStatistics [MSC 2020]$3VANC022998$2MF 610 $aHigh Stochastic Dimension$9KW:K 610 $aMCMC Methods$9KW:K 610 $aMaximum Entropy Principle$9KW:K 610 $aModel Uncertainties$9KW:K 610 $aModel-parameter Uncertainties$9KW:K 610 $aNon-Gaussian Random Fields$9KW:K 610 $aNonparametric Uncertainties$9KW:K 610 $aPolynomial Chaos Expansion$9KW:K 610 $aRandom matrices$9KW:K 610 $aRobust Design$9KW:K 610 $aStatistical inverse problems$9KW:K 620 $aCH$dCham$3VANL001889 700 1$aSoize$bChristian$3VANV094814$029246 712 $aSpringer $3VANV108073$4650 801 $aIT$bSOL$c20240614$gRICA 856 4 $uhttp://doi.org/10.1007/978-3-319-54339-0$zE-book ? Accesso al full-text attraverso riconoscimento IP di Ateneo, proxy e/o Shibboleth 899 $aBIBLIOTECA DEL DIPARTIMENTO DI MATEMATICA E FISICA$1IT-CE0120$2VAN08 912 $fN 912 $aVAN0123409 950 $aBIBLIOTECA DEL DIPARTIMENTO DI MATEMATICA E FISICA$d08CONS e-book 0965 $e08eMF965 20190919 996 $aUncertainty quantification$91560479 997 $aUNICAMPANIA