Results 91 to 100 of about 10,800,365 (307)

A Generalization of Markov Processes

open access: yesThe Annals of Probability, 1978
Osterwalder-Schrader (OS) positive symmetric stationary stochastic processes are discussed. A natural construction is given for the associated positive semigroup structure. Conversely, OS-positive symmetric stationary stochastic processes are constructed from positive semigroup structures. OS-positive processes are seen to be the natural generalization
openaire   +2 more sources

The Lévy–Khintchine type operators with variable Lipschitz continuous coefficients generate linear or nonlinear Markov processes and semigroups [PDF]

open access: yes, 2011
Ito's construction of Markovian solutions to stochastic equations driven by a Lévy noise is extended to nonlinear distribution dependent integrands aiming at the effective construction of linear and nonlinear Markov semigroups and the corresponding ...
Kolokoltsov, V. N. (Vasiliĭ Nikitich)
core   +1 more source

MAPA: A Semantic Network Framework for Functional Module Discovery and Interpretation in Multi‐Omics Data

open access: yesAdvanced Science, EarlyView.
MAPA transforms complex multi‐omics data into biologically coherent functional modules by integrating pathway information with molecular interaction networks. Retrieval‐augmented large language models then generate structured, literature‐informed interpretations.
Yifei Ge   +13 more
wiley   +1 more source

A Generalized ARFIMA Process with Markov-Switching Fractional Differencing Parameter [PDF]

open access: yes
We propose a general class of Markov-switching-ARFIMA processes in order to combine strands of long memory and Markov-switching literature. Although the coverage of this class of models is broad, we show that these models can be easily estimated with the
Wolfgang Härdle, Wen-Jen Tsay
core  

Applied semi-Markov process

open access: yes, 2005
Applied Semi-Markov Processes aims to give to the reader the tools necessary to apply semi-Markov processes in real-life problems. The book is self-contained and, starting from a low level of probability concepts, gradually brings the reader to a deep ...
Manca, Raimondo   +2 more
core   +1 more source

Variance bounding and geometric ergodicity of Markov chain Monte Carlo kernels for approximate Bayesian computation [PDF]

open access: yes, 2014
Approximate Bayesian computation has emerged as a standard computational tool when dealing with intractable likelihood functions in Bayesian inference. We show that many common Markov chain Monte Carlo kernels used to facilitate inference in this setting
Łatuszyński, Krzysztof, Lee, Anthony
core   +1 more source

Exceptional Antimodes in Multi‐Drive Cavity Magnonics

open access: yesAdvanced Electronic Materials, EarlyView.
Driven‐dissipative cavity‐magnonics provides a flexible platform for engineering non‐Hermitian physics such as exceptional points. Here, using a four‐port, three‐mode system with controllable microwave interference, antimodes and coherent perfect extinction (CPE) are realized, enabling active tuning to antimode exceptional points.
Mawgan A. Smith   +4 more
wiley   +1 more source

Collisions of Markov Processes

open access: yesTokyo Journal of Mathematics, 1995
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
openaire   +4 more sources

Robot introspection through learned hidden Markov models [PDF]

open access: yes, 2006
In this paper we describe a machine learning approach for acquiring a model of a robot behaviour from raw sensor data. We are interested in automating the acquisition of behavioural models to provide a robot with an introspective capability.
Maria Fox   +11 more
core   +2 more sources

From Top to Bottom: Manufacturing Process‐Context Aware Resolution of Energy Device Electrodes Through a 3D Diffusion Generative Model

open access: yesAdvanced Energy Materials, EarlyView.
The application of a generative diffusion model, enhanced with a training data augmentation pipeline retaining the manufacturing process context of electrode microstructures, leads to improved fidelity of the through‐plane tortuosity factor in the AI generated samples.
Victor Ramirez‐Camacho   +5 more
wiley   +1 more source

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