Zobrazeno 1 - 10
of 288
pro vyhledávání: '"Di Persio, Luca"'
Autor:
Alruqimi, Mohammed, Di Persio, Luca
Despite numerous research efforts in applying deep learning to time series forecasting, achieving high accuracy in multi-step predictions for volatile time series like crude oil prices remains a significant challenge. Moreover, most existing approach
Externí odkaz:
http://arxiv.org/abs/2407.11267
Autor:
Alruqimi, Mohammed, Di Persio, Luca
Accurate crude oil price forecasting is crucial for various economic activities, including energy trading, risk management, and investment planning. Although deep learning models have emerged as powerful tools for crude oil price forecasting, achievi
Externí odkaz:
http://arxiv.org/abs/2407.12062
This article presents an innovative approach to integrating port-Hamiltonian systems with neural network architectures, transitioning from deterministic to stochastic models. The study presents novel mathematical formulations and computational models
Externí odkaz:
http://arxiv.org/abs/2403.16737
We study a general class of interacting particle systems over a countable state space $V$ where on each site $x \in V$ the particle mass $\eta(x) \geq 0$ follows a stochastic differential equation. We construct the corresponding Markovian dynamics in
Externí odkaz:
http://arxiv.org/abs/2308.07838
Autor:
Di Persio, Luca, Kuchling, Peter
In this article, we analyse the existence of an optimal feedback controller of stochastic optimal control problems governed by SDEs which have the control in the diffusion part. To this end, we consider the underlying Fokker-Planck equation to transf
Externí odkaz:
http://arxiv.org/abs/2305.09379
We study classical continuous systems with singular distributions of velocities. These distributions are given by Radon measures with the infinite mass. Positions of particles, in such systems, are no more usual configurations in the location space,
Externí odkaz:
http://arxiv.org/abs/2212.11902
We consider a generalization of classical results of Freidlin and Wentzell to the case of time dependent dissipative drifts. We show the convergence of diffusions with multiplicative noise in the zero limit of a diffusivity parameter to the related d
Externí odkaz:
http://arxiv.org/abs/2211.03839
We introduce a framework that allows to employ (non-negative) measure-valued processes for energy market modeling, in particular for electricity and gas futures. Interpreting the process' spatial structure as time to maturity, we show how the Heath-J
Externí odkaz:
http://arxiv.org/abs/2210.09331
We consider a system of Forward Backward Stochastic Differential Equations (FBSDEs), with time delayed generator and driven by L\`evy-type noise. We establish a non linear Feynman Kac representation formula associating the solution given by the FBSDE
Externí odkaz:
http://arxiv.org/abs/2209.06097
We study stochastic differential equations(SDEs) with a small perturbation parameter. Under the dissipative condition on the drift coefficient and the local Lipschitz condition on the drift and diffusion coefficients we prove the existence and unique
Externí odkaz:
http://arxiv.org/abs/2205.01750