Bibliothèque de L'IMIST/CNRST

An Application of Gaussian Measures to Functional Analysis -- Stochastic Taylor Formulas and Riemannian Geometry -- Local invertibility of adapted shifts on Wiener Space and related topics -- Dilation vector field on Wiener space -- The calculus of differentials for the weak Stratonovich integral -- Large deviations for Hilbert space valued Wiener processes: a sequence space approach -- Stationary distributions for jump processes with inert drift -- An Ornstein-Uhlenbeck type process which satisfies sufficient conditions for a simulation based filtering procedure -- Escape probability for stochastic dynamical systems with jumps -- On Stochastic Navier-Stokes Equation Driven by Stationary White Noise -- Intermittency and chaos for a non-linear stochastic wave equation in dimension 1 -- Generalized stochastic heat equations -- Gaussian Upper Density estimates for spatially homogeneous Stochastic PDEs -- Stationarity of the solution for the semilinear stochastic integral equation on the whole real line -- A strong approximation of sub-fractional Brownian motion by means of transport processes -- Malliavin calculus for fractional heat equation -- Parameter estimation for alpha-fractional bridges -- Gradient bounds for solutions of stochastic differential equations driven by fractional Brownian motion -- Parameter estimation for fractional Ornstein-Uhlenbeck processes with discrete observations -- The effect of competition on the height and length of the forest of genealogical trees of a large population -- Linking progressive and initial filtration expansions -- A Malliavin calculus approach to general stochastic differential games with partial information -- Asymptotics for the Length of Longest Increasing Subsequences of Binary Markovian Words -- A short rate model using ambit processes -- Parametric regularity of the conditional expectations via the Malliavin calculus and applications.

The stochastic calculus of variations of Paul Malliavin (1925 - 2010), known today as the Malliavin Calculus, has found many applications, within and beyond the core mathematical discipline. Stochastic analysis provides a fruitful interpretation of this calculus, particularly as described by David Nualart and the scores of mathematicians he influences and with whom he collaborates. Many of these, including leading stochastic analysts and junior researchers, presented their cutting-edge research at an international conference in honor of David Nualart's career, on March 19-21, 2011, at the University of Kansas, USA. These scholars and other top-level mathematicians have kindly contributed research articles for this refereed volume.