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This paper concerns the explicit treatment of substitutions in the lambda calculus. One of its contributions is the simplification and rationalization of the suspension calculus that embodies such a treatment. The earlier version of this…

Logic in Computer Science · Computer Science 2007-05-23 Andrew Gacek , Gopalan Nadathur

We develop a non-anticipating calculus of variations for functionals on a space of laws of continuous semi-martingales, which extends the classical one. We extend Hamilton's least action principle and Noether's theorem to this generalized…

Probability · Mathematics 2015-01-22 Ana Bela Cruzeiro , Rémi Lassalle

The concept of stochastic Lagrangian and its use in statistical dynamics is illustrated theoretically, and with some examples. Dynamical variables undergoing stochastic differential equations are stochastic processes themselves, and their…

Statistical Mechanics · Physics 2020-03-18 Massimo Materassi

Machine learning provides algorithms that can learn from data and make inferences or predictions on data. Stochastic acceptors or probabilistic automata are stochastic automata without output that can model components in machine learning…

Machine Learning · Computer Science 2018-12-27 Karl-Heinz Zimmermann

Stochastic simulation can make the molecular processes of cellular control more vivid than the traditional differential-equation approach by generating typical system histories instead of just statistical measures such as the mean and…

Subcellular Processes · Quantitative Biology 2018-09-18 Kevin Y. Chen , Daniel M. Zuckerman , Philip C. Nelson

We exhibit conditions under which the flow of marginal distributions of a discontinuous semimartingale $\xi$ can be matched by a Markov process, whose infinitesimal generator is expressed in terms of the local characteristics of $\xi$. Our…

Probability · Mathematics 2012-05-17 Amel Bentata , Rama Cont

We leverage commutative hypercomplex analysis to find closed-form solutions of some systems of stochastic differential equations. Specifically, we obtain necessary and sufficient conditions under which a system of stochastic differential…

Probability · Mathematics 2017-01-25 Celestin Wafo Soh , Fazal M Mahomed

The martingale comparison method is extended to derive comparison results for path-independent functions for general semimartingales. Our approach allows to dismiss with the Markovian assumption on one of the processes made in previous…

Probability · Mathematics 2019-08-28 Benedikt Köpfer , Ludger Rüschendorf

Monte Carlo simulations are based on the manipulation of random numbers to evaluate probable outcomes, with applicability in a variety of different fields. By assigning probabilities, which can be determined a priori, to various events, it…

Physics Education · Physics 2022-01-03 Parasuraman Swaminathan

This article proposes an artificial data generating algorithm that is simple and easy to customize. The fundamental concept is to perform random permutation of Monte Carlo generated random numbers which conform to the unconditional…

Computational Finance · Quantitative Finance 2021-02-17 A. Christian Silva , Fernando F. Ferreira

The modelling and analysis of biological systems has deep roots in Mathematics, specifically in the field of Ordinary Differential Equations. Alternative approaches based on formal calculi, often derived from process algebras or term…

We introduce a functional calculus with simple syntax and operational semantics in which the calculi introduced so far in the Curry-Howard correspondence for Classical Logic can be faithfully encoded. Our calculus enjoys confluence without…

Logic in Computer Science · Computer Science 2013-04-01 Alberto Carraro , Thomas Ehrhard , Antonino Salibra

We develop a stochastic calculus for processes which are built by convoluting a pure jump, zero expectation L\'{e}vy process with a Volterra-type kernel. This class of processes contains, for example, fractional L\'{e}vy processes as…

Probability · Mathematics 2008-12-18 Christian Bender , Tina Marquardt

The covariance function of a Gauss-Markov process evaluated at points $(s,t)$ admits a representation as a product of a function of $\min(s,t)$ and a function of $\max(s,t)$. We call these functions the covariance factors of a Gauss-Markov…

Probability · Mathematics 2025-08-01 Georges Kassis

The main object of investigation in this paper is a very general regression model in optional setting - when an observed process is an optional semimartingale depending on an unknown parameter. It is well-known that statistical data may…

Statistics Theory · Mathematics 2021-03-16 Mohamed Abdelghani , Alexander Melnikov , Andrey Pak

This paper introduces a mathematical framework of a stochastic process model as a generalization of diffusion stochastic processes to model latent variables in categorical responses given unobserved random effects and maximum likelihood…

Statistics Theory · Mathematics 2023-06-05 Mahdi Mollakazemiha

We describe an adaptive importance sampling algorithm for rare events that is based on a dual stochastic control formulation of a path sampling problem. Specifically, we focus on path functionals that have the form of cumulate generating…

Dynamical Systems · Mathematics 2019-01-30 Omar Kebiri , Lara Neureither , Carsten Hartmann

The Calculus of Wrapped Compartments (CWC) is a variant of the Calculus of Looping Sequences (CLS). While keeping the same expressiveness, CWC strongly simplifies the development of automatic tools for the analysis of biological systems.…

Computational Engineering, Finance, and Science · Computer Science 2010-06-29 Mario Coppo , Ferruccio Damiani , Maurizio Drocco , Elena Grassi , Angelo Troina

In this work we introduce a theory of stochastic integration with respect to general cylindrical semimartingales defined on a locally convex space $\Phi$. Our construction of the stochastic integral is based on the theory of tensor products…

Probability · Mathematics 2021-12-06 C. A. Fonseca-Mora

The ability to persist in the spacial environment is, not only in the robotic context, an essential feature. Positional knowledge is one of the most important aspects of space and a number of methods to represent these information have been…

Artificial Intelligence · Computer Science 2019-11-18 Sören Schwertfeger
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