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Discovering the underlying relationships among variables from temporal observations has been a longstanding challenge in numerous scientific disciplines, including biology, finance, and climate science. The dynamics of such systems are…

Machine Learning · Computer Science 2024-05-07 Benjie Wang , Joel Jennings , Wenbo Gong

In this manuscript we consider Intrinsic Stochastic Differential Equations on manifolds and constrain it to a level set of a smooth function. Such type of constraints are known as explicit algebraic constraints. The system of differential…

Probability · Mathematics 2023-07-28 Sumit Suthar , Soumyendu Raha

Astronomical time series from large-scale surveys like LSST are often irregularly sampled and incomplete, posing challenges for classification and anomaly detection. We introduce a new framework based on Neural Stochastic Delay Differential…

Machine Learning · Computer Science 2026-04-03 YongKyung Oh , Seungsu Kam , Dong-Young Lim , Sungil Kim

By developing new efficient techniques and using an appropriate fixed point theorem, we derive several new sufficient conditions for the pseudo almost periodic solutions with double measure for some system of differential equations with…

Analysis of PDEs · Mathematics 2020-03-11 Mohsen Miraoui , Dušan D. Repovš

Rate-independent systems allow for solutions with jumps that need additional modeling. Here we suggest a formulation that arises as limit of viscous regularization of the solutions in the extended state space. Hence, our parametrized metric…

Analysis of PDEs · Mathematics 2008-07-08 Alexander Mielke , Riccarda Rossi , Giuseppe Savaré

The intersection of machine learning and dynamical systems has generated considerable interest recently. Neural Ordinary Differential Equations (NODEs) represent a rich overlap between these fields. In this paper, we develop a continuous…

Optimization and Control · Mathematics 2023-06-16 Maria Oprea , Mark Walth , Robert Stephany , Gabriella Torres Nothaft , Arnaldo Rodriguez-Gonzalez , William Clark

In this paper, we introduce a model-based deep-learning approach to solve finite-horizon continuous-time stochastic control problems with jumps. We iteratively train two neural networks: one to represent the optimal policy and the other to…

Machine Learning · Computer Science 2026-01-16 Patrick Cheridito , Jean-Loup Dupret , Donatien Hainaut

This work focuses on multivalued stochastic differential equations with jumps. First, by employing the weak convergence approach, we establish the Freidlin-Wentzell uniform large deviation principle and the Dembo-Zeitouni uniform large…

Probability · Mathematics 2025-12-23 Huijie Qiao

A numerical approach for the approximation of inertial manifolds of stochastic evolutionary equations with multiplicative noise is presented and illustrated. After splitting the stochastic evolutionary equations into a backward and a…

Dynamical Systems · Mathematics 2012-06-22 Xingye Kan , Jinqiao Duan , Ioannis G. Kevrekidis , Anthony J. Roberts

In this paper, we investigate the problem of strong approximation of the solutions of stochastic differential equations (SDEs) when the drift coefficient is given in integral form. We investigate its upper error bounds, in terms of the…

Numerical Analysis · Mathematics 2025-11-20 Paweł Przybyłowicz , Michał Sobieraj

We study the discrete-time approximation for solutions of quadratic forward back- ward stochastic differential equations (FBSDEs) driven by a Brownian motion and a jump process which could be dependent. Assuming that the generator has a…

Optimization and Control · Mathematics 2012-11-28 Idris Kharroubi , Thomas Lim

We study a stochastic differential equation with an unbounded drift and general H\"older continuous noise of an arbitrary order. The corresponding equation turns out to have a unique solution that, depending on a particular shape of the…

Probability · Mathematics 2021-12-15 Giulia Di Nunno , Yuliya Mishura , Anton Yurchenko-Tytarenko

This paper studies open-loop equilibriums for a general class of time-inconsistent stochastic control problems under jump-diffusion SDEs with deterministic coefficients. Inspired by the idea of Four-Step-Scheme for forward-backward…

Optimization and Control · Mathematics 2020-08-18 Ishak Alia

Simulating stochastic differential equations (SDEs) in bounded domains, presents significant computational challenges due to particle exit phenomena, which requires accurate modeling of interior stochastic dynamics and boundary…

Machine Learning · Statistics 2025-07-23 Minglei Yang , Yanfang Liu , Diego del-Castillo-Negrete , Yanzhao Cao , Guannan Zhang

Sufficient and necessary conditions are presented for the order-preservation of stochastic functional differential equations on $\R^d$ with non-Lipschitzian coefficients driven by the Brownian motion and Poisson processes. The sufficiency…

Probability · Mathematics 2014-01-22 Xing Huang , Feng-Yu Wang

In this paper we study useful estimates, in particular $L^p$-estimates, for fully coupled forward-backward stochastic differential equations (FBSDEs) with jumps. These estimates are proved at one hand for fully coupled FBSDEs with jumps…

Probability · Mathematics 2013-02-06 Juan Li , Qingmeng Wei

In this paper, we study the existence and uniqueness of solution to a system of nonlinear fully coupled forward-backward doubly stochastic differential equations with Poisson jumps. Our work is established in infinite dimensional separable…

Probability · Mathematics 2024-07-12 AbdulRahman Al-Hussein

In this paper we introduce a model, the stochastic fractional delay differential equation (SFDDE), which is based on the linear stochastic delay differential equation and produces stationary processes with hyperbolically decaying…

Probability · Mathematics 2018-06-21 Richard A. Davis , Mikkel Slot Nielsen , Victor Rohde

Dynamical system models with delayed dynamics and small noise arise in a variety of applications in science and engineering. In many applications, stable equilibrium or periodic behavior is critical to a well functioning system. Sufficient…

Probability · Mathematics 2017-10-27 David Lipshutz

In this paper, we establish a result for existence and uniqueness of stochastic differential equations on Riemannian manifolds, for regular inhomogeneous tensor coefficients with stochastic drift, under geometrical hypothesis on the…

Probability · Mathematics 2025-05-07 Matthias Rakotomalala