LEADER 03268nam0 2200661 i 450 001 VAN0124581 005 20230628122303.715 017 70$2N$a9783319911434 100 $a20191021d2018 |0itac50 ba 101 $aeng 102 $aCH 105 $a|||| ||||| 200 1 $aBayesian Inference and Maximum Entropy Methods in Science and Engineering$eMaxEnt 37, Jarinu, Brazil, July 09?14, 2017$fAdriano Polpo ... [et al.] editors 210 $aCham$cSpringer$d2018 215 $axvi, 304 p.$cill.$d24 cm 410 1$1001VAN0102574$12001 $aSpringer proceedings in mathematics & statistics$1210 $aBerlin [etc.]$cSpringer$v239 500 1$3VAN0236144$aBayesian Inference and Maximum Entropy Methods in Science and Engineering$91564664 606 $a82B41$xRandom walks, random surfaces, lattice animals, etc. in equilibrium statistical mechanics [MSC 2020]$3VANC020793$2MF 606 $a60G35$xSignal detection and filtering (aspects of stochastic processes) [MSC 2020]$3VANC021485$2MF 606 $a62-XX$xStatistics [MSC 2020]$3VANC022998$2MF 606 $a82B31$xStochastic methods applied to problems in equilibrium statistical mechanics [MSC 2020]$3VANC024273$2MF 606 $a62Axx$xFoundational topics in statistics [MSC 2020]$3VANC025026$2MF 606 $a65Cxx$xProbabilistic methods, stochastic differential equations [MSC 2020]$3VANC028329$2MF 606 $a81Pxx$xFoundations, quantum information and its processing, quantum axioms, and philosophy [MSC 2020]$3VANC029592$2MF 606 $a62Fxx$xParametric inference [MSC 2020]$3VANC031220$2MF 606 $a85A35$xStatistical astronomy [MSC 2020]$3VANC033594$2MF 610 $aAstrophysics$9KW:K 610 $aBiostatistics$9KW:K 610 $aChemistry$9KW:K 610 $aClimate Studies$9KW:K 610 $aCommunications Theory$9KW:K 610 $aComology$9KW:K 610 $aEarth Science$9KW:K 610 $aEntropy$9KW:K 610 $aFluid mechanics$9KW:K 610 $aGenetics$9KW:K 610 $aGeophysics$9KW:K 610 $aImprecise Probability$9KW:K 610 $aMachine learning$9KW:K 610 $aMaterial Science$9KW:K 610 $aMaximum Entropy$9KW:K 610 $aMedical Imaging$9KW:K 610 $aNon-parametric Mmethods$9KW:K 610 $aRobotics$9KW:K 610 $aStatistical models$9KW:K 610 $aSurvival analysis$9KW:K 620 $aCH$dCham$3VANL001889 702 1$aPolpo$bAdriano$3VANV087415 712 12$aInternational Workshop on Bayesian Inference and Maximum Entropy Methods in Science and Engineering$d37.$f2017$eJarinu, Brazil$3VANV096006 712 $aSpringer $3VANV108073$4650 801 $aIT$bSOL$c20240614$gRICA 856 4 $uhttp://doi.org/10.1007/978-3-319-91143-4$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 $aVAN0124581 950 $aBIBLIOTECA DEL DIPARTIMENTO DI MATEMATICA E FISICA$d08CONS e-book 1048 $e08eMF1048 20191021 996 $aBayesian Inference and Maximum Entropy Methods in Science and Engineering$91564664 997 $aUNICAMPANIA