Results 51 to 60 of about 17,102 (166)
Reinforcement Learning for Jump‐Diffusions, With Financial Applications
Mathematical Finance, EarlyView.ABSTRACT We study continuous‐time reinforcement learning (RL) for stochastic control in which system dynamics are governed by jump‐diffusion processes. We formulate an entropy‐regularized exploratory control problem with stochastic policies to capture the exploration–exploitation balance essential for RL.
Xuefeng Gao, Lingfei Li, Xun Yu Zhou
wiley +1 more source
Mathematical Finance, EarlyView.ABSTRACT This study develops a novel multivariate stochastic framework for assessing systemic risks, such as climate and nature‐related shocks, within production or financial networks. By embedding a linear stochastic fluid network, interpretable as a generalized vector Ornstein–Uhlenbeck process, into the production network of interdependent ...
Giovanni Amici +3 more
wiley +1 more source
, 2010 We aim at characterizing viability, invariance and some reachability properties of controlled piecewise deterministic Markov processes (PDMPs). Using analytical methods from the theory of viscosity solutions, we establish criteria for viability and ...
Goreac, D.
core +4 more sources
Journal of Time Series Analysis, Volume 47, Issue 3, Page 727-748, May 2026.ABSTRACT We consider the problem of sequential (online) estimation of a single change point in a piecewise linear regression model under a Gaussian setup. We demonstrate that certain CUSUM‐type statistics attain the minimax optimal rates for localizing the change point.
Annika Hüselitz, Housen Li, Axel Munk
wiley +1 more source
MathematicsThis paper analyzes a finite-capacity GI/M/2/N queue with two heterogeneous servers operating under a multiple working-vacation policy, Bernoulli feedback, and customer impatience.
Abdelhak Guendouzi, Salim Bouzebda
doaj +1 more source
On time reversal of piecewise deterministic Markov processes
Electronic Journal of Probability, 2013 We study the time reversal of a general PDMP. The time reversed process is defined as $X_{(T-t)-}$, where $T$ is some given time and $X_t$ is a stationary PDMP. We obtain the parameters of the reversed process, like the jump intensity and the jump measure.
Löpker, Andreas, Palmowski, Zbigniew
openaire +4 more sources
Causal Inference for Geostatistical Data Using an INLA‐based Spatial Propensity Score
Environmetrics, Volume 37, Issue 3, April 2026.ABSTRACT In this paper, we propose a Bayesian approach for spatial causal inference based on combining spatial propensity scoring with Integrated Nested Laplace Approximation. The method models both local and spillover exposure effects via multiple likelihoods and treats counterfactuals as missing data, allowing inference also for non‐Gaussian outcomes.
Chiara Di Maria +3 more
wiley +1 more source
New Journal of PhysicsTopological phases have been a central focus of condensed-matter physics for over 50 years. Along with many experimental applications, they have provided much intellectual interest due to their characterization via some form of topological ordering, as ...
Michael F Faulkner
doaj +1 more source
, 2015 We aim at characterizing the asymptotic behavior of value functions in the control of piece-wise deterministic Markov processes (PDMP) of switch type under nonexpansive assumptions.
Goreac, Dan
core +4 more sources
Hybrid Reaction–Diffusion Epidemic Models: Dynamics and Emergence of Oscillations
Mathematical Methods in the Applied Sciences, Volume 49, Issue 5, Page 4074-4095, 30 March 2026.ABSTRACT In this paper, we construct a hybrid epidemic mathematical model based on a reaction–diffusion system of the SIR (susceptible‐infected‐recovered) type. This model integrates the impact of random factors on the transmission rate of infectious diseases, represented by a probabilistic process acting at discrete time steps.
Asmae Tajani +2 more
wiley +1 more source