LEADER 03520nam 2200673 450 001 996466624503316 005 20220420122913.0 010 $a3-540-68513-8 024 7 $a10.1007/BFb0093175 035 $a(CKB)1000000000437385 035 $a(SSID)ssj0000325848 035 $a(PQKBManifestationID)12118500 035 $a(PQKBTitleCode)TC0000325848 035 $a(PQKBWorkID)10264733 035 $a(PQKB)10592690 035 $a(DE-He213)978-3-540-68513-5 035 $a(MiAaPQ)EBC5591936 035 $a(MiAaPQ)EBC6691590 035 $a(Au-PeEL)EBL5591936 035 $a(OCoLC)1066194463 035 $a(Au-PeEL)EBL6691590 035 $a(PPN)155197592 035 $a(EXLCZ)991000000000437385 100 $a20220420d1996 uy 0 101 0 $aeng 135 $aurnn|008mamaa 181 $ctxt 182 $cc 183 $acr 200 00$aProbabilistic models for nonlinear partial differential equations $electures given at the 1st session of the Centro internazionale matematico estivo (C.I.M.E.) held in Montecatini Terme, Italy, May 22-30, 1995 /$fC. Graham, D. Talay, L. Tubaro (editors) 205 $a1st ed. 1996. 210 1$aBerlin, Germany ;$aNew York, New York :$cSpringer,$d[1996] 210 4$dİ1996 215 $a1 online resource (X, 302 p.) 225 1 $aC.I.M.E. Foundation Subseries ;$v1627 300 $aBibliographic Level Mode of Issuance: Monograph 311 $a3-540-61397-8 320 $aIncludes bibliographical references. 327 $aWeak convergence of stochastic integrals and differential equations -- Asymptotic behaviour of some interacting particle systems; McKean-Vlasov and Boltzmann models -- Kinetic limits for stochastic particle systems -- A statistical physics approach to large networks -- Probabilistic numerical methods for partial differential equations: Elements of analysis -- Weak convergence of stochastic integrals and differential equations II: Infinite dimensional case. 330 $aThe lecture courses of the CIME Summer School on Probabilistic Models for Nonlinear PDE's and their Numerical Applications (April 1995) had a three-fold emphasis: first, on the weak convergence of stochastic integrals; second, on the probabilistic interpretation and the particle approximation of equations coming from Physics (conservation laws, Boltzmann-like and Navier-Stokes equations); third, on the modelling of networks by interacting particle systems. This book, collecting the notes of these courses, will be useful to probabilists working on stochastic particle methods and on the approximation of SPDEs, in particular, to PhD students and young researchers. 410 0$aC.I.M.E. Foundation Subseries ;$v1627 606 $aConvergence$vCongresses 606 $aDifferential equations, Nonlinear$xNumerical solutions$vCongresses 606 $aStochastic partial differential equations$xNumerical solutions$vCongresses 615 0$aConvergence 615 0$aDifferential equations, Nonlinear$xNumerical solutions 615 0$aStochastic partial differential equations$xNumerical solutions 676 $a519.2 702 $aGraham$b C$g(Carl), 702 $aTalay$b D$g(Denis), 702 $aTubaro$b L$g(Luciano),$f1947- 712 02$aCentro internazionale matematico estivo. 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a996466624503316 996 $aProbabilistic models for nonlinear partial differential equations$92834691 997 $aUNISA