Zobrazeno 1 - 10
of 4 429
pro vyhledávání: '"Crişan TO"'
Autor:
Crisan, Dan, Pardoux, Etienne
Nonlinear filtering is a pivotal problem that has attracted significant attention from mathematicians, statisticians, engineers, and various other scientific disciplines. The solution to this problem is governed by the so-called filtering equations.
Externí odkaz:
http://arxiv.org/abs/2411.11125
There is a history of simple forecast error growth models designed to capture the key properties of error growth in operational numerical weather prediction (NWP) models. We propose here such a scalar model that relies on the previous ones and incorp
Externí odkaz:
http://arxiv.org/abs/2411.06623
We use a rough path-based approach to investigate the degeneracy problem in the context of pathwise control. We extend the framework developed in arXiv:1902.05434 to treat admissible controls from a suitable class of H\"older continuous paths and sim
Externí odkaz:
http://arxiv.org/abs/2411.05488
Data assimilation plays a crucial role in numerical modeling, enabling the integration of real-world observations into mathematical models to enhance the accuracy and predictive capabilities of simulations. This approach is widely applied in fields s
Externí odkaz:
http://arxiv.org/abs/2411.04140
Nudging is a popular algorithmic strategy in numerical filtering to deal with the problem of inference in high-dimensional dynamical systems. We demonstrate in this paper that general nudging techniques can also tackle another crucial statistical pro
Externí odkaz:
http://arxiv.org/abs/2411.00218
Autor:
Giovagnini, Filippo, Crisan, Dan
We study a model of interacting particles represented by a system of N stochastic differential equations. We establish that the mollified empirical distribution of the system converges uniformly with respect to both time and spatial variables to the
Externí odkaz:
http://arxiv.org/abs/2410.23163
Autor:
Crisan, Dan, Clark, Martin
This paper studies the identification of an $\mathbb{R}^d$-valued diffusion $X$ when a running function of it, say $h(X_t)$, is observed. A point-wise observation of the process (in other words, observing $h(X_t)$ in isolation) cannot identify $X_t$
Externí odkaz:
http://arxiv.org/abs/2410.17737
In this paper, we introduce a new classical fractional particle model incorporating fractional first derivatives. This model represents a natural extension of the standard classical particle with kinetic energy being quadratic in fractional first der
Externí odkaz:
http://arxiv.org/abs/2407.14552
This paper is devoted to the problem of approximating non-linear Stochastic Partial Differential Equations (SPDEs) via interacting particle systems. In particular, we consider the Stochastic McKean-Vlasov equation, which is the McKean-Vlasov (MKV) PD
Externí odkaz:
http://arxiv.org/abs/2404.07488
In recent work, the authors have developed a generic methodology for calibrating the noise in fluid dynamics stochastic partial differential equations where the stochasticity was introduced to parametrize subgrid-scale processes. The stochastic param
Externí odkaz:
http://arxiv.org/abs/2403.10578