Linear reflected backward stochastic differential equations arising from vulnerable claims in markets with random horizon [0.03%]
随机时间 horizon 的市场中易毁债券的倒向随机方程
Tahir Choulli,Safa&#x; Alsheyab
Tahir Choulli
This paper considers the setting governed by ( F , τ ) , where F is the "public" flow of information, and τ is a random time which might not be F -observable. This framework covers credit risk and life insurance. In this setting, F is...
Weak persistence and extinction of a stochastic epidemic model with distributed delay and Ornstein-Uhlenbeck process [0.03%]
具有分布式时滞和奥恩斯坦-乌伦贝克过程的随机传染病模型的弱持续性和灭绝性
Yanyang Sun,Chao Liu,Lora Cheung
Yanyang Sun
A stochastic distributed delay epidemic model with Markovian switching and Allee effect is constructed, where the infectious disease transmission rate follows a mean-reverting Ornstein-Uhlenbeck process. Hybrid dynamic effects of Ornstein-U...
Connecting image inpainting with denoising in the homogeneous diffusion setting [0.03%]
均匀扩散设定下图像修复与去噪的联系
Daniel Gaa,Vassillen Chizhov,Pascal Peter et al.
Daniel Gaa et al.
While local methods for image denoising and inpainting may use similar concepts, their connections have hardly been investigated so far. The goal of this work is to establish links between the two by focusing on the most foundational scenar...
A unified stochastic SIR model driven by Lévy noise with time-dependency [0.03%]
一个由Lévy噪声驱动的时间依赖性统一随机SIR模型
Terry Easlick,Wei Sun
Terry Easlick
We propose a unified stochastic SIR model driven by Lévy noise. The model is structural enough to allow for time-dependency, nonlinearity, discontinuity, demography, and environmental disturbances. We present concise results on the existen...
Some properties of branching processes with random control functions and affected by viral infectivity in random environments [0.03%]
随机控制函数且受随机环境中病毒传染性影响的分枝过程的某些性质
Min Ren,Guanghui Zhang
Min Ren
In this paper, a model of branching processes with random control functions and affected by viral infectivity in independent and identically distributed random environments is established, and the Markov property of the model and a sufficie...
A fast continuous time approach with time scaling for nonsmooth convex optimization [0.03%]
非光滑凸优化问题的一种快速连续时间积分方法及时间尺度变换
Radu Ioan Boţ,Mikhail A Karapetyants
Radu Ioan Boţ
In a Hilbert setting, we study the convergence properties of the second order in time dynamical system combining viscous and Hessian-driven damping with time scaling in relation to the minimization of a nonsmooth and convex function. The sy...
A physics-informed neural network to model COVID-19 infection and hospitalization scenarios [0.03%]
一种物理信息神经网络，用于建模COVID-19感染和住院情况
Sarah Berkhahn,Matthias Ehrhardt
Sarah Berkhahn
In this paper, we replace the standard numerical approach of estimating parameters in a mathematical model using numerical solvers for differential equations with a physics-informed neural network (PINN). This neural network requires a sequ...
Dynamics analysis and optimal control of SIVR epidemic model with incomplete immunity [0.03%]
具有不完全免疫的SIVR流行病模型的动力学分析与最优控制
Yiming Liu,Shuang Jian,Jianguo Gao
Yiming Liu
In this paper, we establish an SIVR model with diffusion, spatially heterogeneous, latent infection, and incomplete immunity in the Neumann boundary condition. Firstly, the threshold dynamic behavior of the model is proved by using the oper...
Uniform convergence guarantees for the deep Ritz method for nonlinear problems [0.03%]
非线性问题深度Ritz方法的一致收敛性保证
Patrick Dondl,Johannes Müller,Marius Zeinhofer
Patrick Dondl
We provide convergence guarantees for the Deep Ritz Method for abstract variational energies. Our results cover nonlinear variational problems such as the p-Laplace equation or the Modica-Mortola energy with essential or natural boundary co...
Global stability of an SAIRD epidemiological model with negative feedback [0.03%]
具有负反馈的SAIRD流行病学模型的全局稳定性
Roxana López-Cruz
Roxana López-Cruz
In this work, we study the dynamical behavior of a modified SIR epidemiological model by introducing negative feedback and a nonpharmaceutical intervention. The first model to be defined is the usceptible-Isolated-Infected-Recovered-Dead (S...