Zobrazeno 1 - 10
of 278 011
pro vyhledávání: '"P. Markov"'
Autor:
Wang, Feng-Yu
In this paper we introduce some recent progresses on the convergence rate in Wasserstein distance for empirical measures of Markov processes. For diffusion processes on compact manifolds possibly with reflecting or killing boundary conditions, the sh
Externí odkaz:
http://arxiv.org/abs/2411.12996
We develop an excursion theory that describes the evolution of a Markov process indexed by a Levy tree away from a regular and instantaneous point $x$ of the state space. The theory builds upon a notion of local time at $x$ that was recently introduc
Externí odkaz:
http://arxiv.org/abs/2411.12717
Autor:
Brandner, Kay
The visible dynamics of small-scale systems are strongly affected by unobservable degrees of freedom, which can belong either to external environments or internal subsystems and almost inevitably induce memory effects. Formally, such inaccessible deg
Externí odkaz:
http://arxiv.org/abs/2411.12596
Autor:
Azeraf, Elie
The Pairwise Markov Chain (PMC) is a probabilistic graphical model extending the well-known Hidden Markov Model. This model, although highly effective for many tasks, has been scarcely utilized for continuous value prediction. This is mainly due to t
Externí odkaz:
http://arxiv.org/abs/2411.11838
This paper deals with the computation of a non-asymptotic lower bound by means of the nonanticipative rate-distortion function (NRDF) on the discrete-time zero-delay variable-rate lossy compression problem for discrete Markov sources with per-stage,
Externí odkaz:
http://arxiv.org/abs/2411.11698
Autor:
Zhang, Xingjian, Wang, Yuhao
Determining potential probability distributions with a given causal graph is vital for causality studies. To bypass the difficulty in characterizing latent variables in a Bayesian network, the nested Markov model provides an elegant algebraic approac
Externí odkaz:
http://arxiv.org/abs/2411.11614
Autor:
Koslik, Jan-Ole
Markov-switching models are powerful tools that allow capturing complex patterns from time series data driven by latent states. Recent work has highlighted the benefits of estimating components of these models nonparametrically, enhancing their flexi
Externí odkaz:
http://arxiv.org/abs/2411.11498
Autor:
Yasinskaya, D. N., Panov, Y. D.
Publikováno v:
Physics of the Solid State 66 (7), 1068 (2024)
We analyze frustrated states of the one-dimensional dilute Ising chain with charged interacting impurities of two types with mapping of the system to some Markov chain. We perform classification and reveal two types of Markov chains: periodic with pe
Externí odkaz:
http://arxiv.org/abs/2411.11319
We consider fair resource allocation in sequential decision-making environments modeled as weakly coupled Markov decision processes, where resource constraints couple the action spaces of $N$ sub-Markov decision processes (sub-MDPs) that would otherw
Externí odkaz:
http://arxiv.org/abs/2411.09804
We develop a method of driving a Markov processes through a continuous flow. In particular, at the level of the transition functions we investigate an approach of adding a first order operator to the generator of a Markov process, when the two genera
Externí odkaz:
http://arxiv.org/abs/2411.09407