We examine the relation between a stochastic version of the rough path integral with the symmetric-Stratonovich integral in the sense of regularization. Under mild regularity conditions in the sense of Malliavin calculus, we establish equality between stochastic rough path and symmetric-Stratonovich integrals driven by a class of Gaussian processes. As a by-product, we show that solutions of multi-dimensional rough differential equations driven by a large class of Gaussian rough paths they are actually solutions to Stratonovich stochastic differential equations. We obtain almost sure convergence rates of the first-order Stratonovich scheme to rough paths integrals in the sense of Gubinelli. In case the time-increment of the Malliavin deriva...
Rough sheets are two-parameter analogs of rough paths. In this work the theory of integration over...
International audienceThe usual way that mathematicians work with randomness is by a rigorous for-mu...
Stochastic Analysis for Gaussian Random Processes and Fields: With Applications presents Hilbert spa...
Given a Gaussian process $X$, its canonical geometric rough path lift $\mathbf{X}$, and a solution $...
We consider additive functionals of stationary Markov processes and show that under Kipnis–Varadhan ...
We develop a stochastic analysis for a Gaussian process $X$ with singular covariance by an intrinsic...
This dissertation contains three research directions. In the first direction, we use rough paths the...
In this thesis new robust integration techniques, which are suitable for various problems from stoch...
We consider two discrete schemes for studying and approximating stochastic differential equations (...
We consider stochastic differential equations of the form dYt=V(Yt)dXt+V0(Yt)dt driven by a multi-di...
43 pagesInternational audienceIn this article, we derive a Stratonovich and Skorohod type change of ...
Let u(t, x), t [epsilon] R, be an adapted process parametrized by a variable x in some metric space ...
We construct a quasi-sure version (in the sense of Malliavin) of geometric rough paths associated wi...
We construct a quasi-sure version (in the sense of Malliavin) of geometric rough paths associated wi...
AbstractLet u(t, x), t ϵ R, be an adapted process parametrized by a variable x in some metric space ...
Rough sheets are two-parameter analogs of rough paths. In this work the theory of integration over...
International audienceThe usual way that mathematicians work with randomness is by a rigorous for-mu...
Stochastic Analysis for Gaussian Random Processes and Fields: With Applications presents Hilbert spa...
Given a Gaussian process $X$, its canonical geometric rough path lift $\mathbf{X}$, and a solution $...
We consider additive functionals of stationary Markov processes and show that under Kipnis–Varadhan ...
We develop a stochastic analysis for a Gaussian process $X$ with singular covariance by an intrinsic...
This dissertation contains three research directions. In the first direction, we use rough paths the...
In this thesis new robust integration techniques, which are suitable for various problems from stoch...
We consider two discrete schemes for studying and approximating stochastic differential equations (...
We consider stochastic differential equations of the form dYt=V(Yt)dXt+V0(Yt)dt driven by a multi-di...
43 pagesInternational audienceIn this article, we derive a Stratonovich and Skorohod type change of ...
Let u(t, x), t [epsilon] R, be an adapted process parametrized by a variable x in some metric space ...
We construct a quasi-sure version (in the sense of Malliavin) of geometric rough paths associated wi...
We construct a quasi-sure version (in the sense of Malliavin) of geometric rough paths associated wi...
AbstractLet u(t, x), t ϵ R, be an adapted process parametrized by a variable x in some metric space ...
Rough sheets are two-parameter analogs of rough paths. In this work the theory of integration over...
International audienceThe usual way that mathematicians work with randomness is by a rigorous for-mu...
Stochastic Analysis for Gaussian Random Processes and Fields: With Applications presents Hilbert spa...