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We consider the inverse problem of reconstructing the posterior measure over the trajec- tories of a diffusion process from discrete time observations and continuous time constraints. We cast the problem in a Bayesian framework and derive…

Machine Learning · Statistics 2016-12-21 Botond Cseke , David Schnoerr , Manfred Opper , Guido Sanguinetti

There is a growing literature adopting a stochastic optimal control (SOC) perspective to fine-tune diffusion models and related generative policies. A prominent class of methods, known as iterative diffusion optimization, solves the SOC…

Optimization and Control · Mathematics 2026-03-24 Yuhang Mei , Amirhossein Taghvaei

We show a concise extension of the monotone stability approach to backward stochastic differential equations (BSDEs) that are jointly driven by a Brownian motion and a random measure for jumps, which could be of infinite activity with a…

Probability · Mathematics 2019-11-21 Dirk Becherer , Martin Büttner , Klebert Kentia

Since the celebrated paper by El Karoui, Peng and Quenez [Mathematical Finance, 7 (1997), 1--71], backward stochastic differential equations have found wide applications in stochastic control, financial technology and machine learning. In…

Probability · Mathematics 2026-02-12 Shengjun Fan , Ying Hu , Shanjian Tang

We present a theory of backward stochastic differential equations in continuous time with an arbitrary filtered probability space. No assumptions are made regarding the left continuity of the filtration, of the predictable quadratic…

Probability · Mathematics 2012-10-15 Samuel N. Cohen , Robert J. Elliott

Generative diffusion models and many stochastic models in science and engineering naturally live in infinite dimensions before discretisation. To incorporate observed data for statistical and learning tasks, one needs to condition on…

Imprecise continuous-time Markov chains are a robust type of continuous-time Markov chains that allow for partially specified time-dependent parameters. Computing inferences for them requires the solution of a non-linear differential…

Probability · Mathematics 2018-10-11 Alexander Erreygers , Jasper De Bock

We extend the construction of equilibria for linear-quadratic and mean-variance portfolio problems available in the literature to a large class of mean-field time-inconsistent stochastic control problems in continuous time. Our approach…

Optimization and Control · Mathematics 2021-10-01 Jiang Yu Nguwi , Nicolas Privault

We study the estimation of the value function for continuous-time Markov diffusion processes using a single, discretely observed ergodic trajectory. Our work provides non-asymptotic statistical guarantees for the least-squares…

Machine Learning · Computer Science 2025-02-07 Wenlong Mou

In [5] the authors obtained Mean-Field backward stochastic differential equations (BSDE) associated with a Mean-field stochastic differential equation (SDE) in a natural way as limit of some highly dimensional system of forward and backward…

Probability · Mathematics 2007-11-21 Rainer Buckdahn , Juan Li , Shige Peng

We consider a non-Markovian optimal stopping problem on finite horizon. We prove that the value process can be represented by means of a backward stochastic differential equation (BSDE), defined on an enlarged probability space, containing…

Probability · Mathematics 2015-02-20 Marco Fuhrman , Huyên Pham , Federica Zeni

Stochastic differential equations and the associated partial differential equations are the cornerstone formalism in stochastic control problems. The universality of bilinear stochastic systems can be found in autonomous systems, non-linear…

Optimization and Control · Mathematics 2019-10-31 Sandhya Rathore , Shambhu Nath Sharma , Dani Juricic

The asymptotic variance is an important criterion to evaluate the performance of Markov chains, especially for the central limit theorems. We give the variational formulas for the asymptotic variance of discrete-time (non-reversible) Markov…

Probability · Mathematics 2020-12-29 Lu-Jing Huang , Yong-Hua Mao

We construct an aggregated version of the value processes associated with stochastic control problems, where the criterion to optimise is given by solutions to semi-martingale backward stochastic differential equations (BSDEs). The results…

Probability · Mathematics 2025-07-03 Dylan Possamaï , Marco Rodrigues , Alexandros Saplaouras

A nonlinear inequality is formulated in the paper. An estimate of the rate of growth/decay of solutions to this inequality is obtained. This inequality is of interest in a study of dynamical systems and nonlinear evolution equations. It can…

Classical Analysis and ODEs · Mathematics 2010-01-29 N. S. Hoang , A. G. Ramm

In this paper we study a family of nonlinear (conditional) expectations that can be understood as a semimartingale with uncertain local characteristics. Here, the differential characteristics are prescribed by a time and path-dependent…

Probability · Mathematics 2023-11-07 David Criens , Lars Niemann

We develop a theory for solving continuous time optimal stopping problems for non-linear expectations. Our motivation is to consider problems in which the stopper uses risk measures to evaluate future rewards.

Optimization and Control · Mathematics 2011-01-11 Erhan Bayraktar , Song Yao

We study approximation of non-autonomous linear differential equations with variable delay over infinite intervals. We use piecewise constant argument to obtain a corresponding discrete difference equation. The study of numerical…

Classical Analysis and ODEs · Mathematics 2016-07-26 Daniel Sepúlveda

In this paper, we study Nash equilibrium payoffs for nonzero-sum stochastic differential games via the theory of backward stochastic differential equations. We obtain an existence theorem and a characterization theorem of Nash equilibrium…

Probability · Mathematics 2011-11-30 Qian Lin

The linear response of a dynamical system refers to changes to properties of the system when small external perturbations are applied. We consider the little-studied question of selecting an optimal perturbation so as to (i) maximise the…

Dynamical Systems · Mathematics 2018-04-04 Fadi Antown , Davor Dragičević , Gary Froyland
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