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Related papers: Information geometry of tempered stable processes

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We develop an information-theoretic approach to isoperimetric inequalities based on entropy dissipation under heat flow. By viewing diffusion as a noisy information channel, we measure how mutual information about set membership decays over…

Differential Geometry · Mathematics 2025-11-20 Amandip Sangha

We introduce a mathematical formulation of feature-informed data assimilation (FIDA). In FIDA, the information about feature events, such as shock waves, level curves, wavefronts and peak value, in dynamical systems are used for the…

Systems and Control · Electrical Eng. & Systems 2022-11-02 Wei Kang , Daniel M. Tartakovsky , Apoorv Srivastava

In many image analysis problems, the contours of objects carry important statistical information about shape. Such contours are typically affected by deformation variables including scaling, translation, rotation, and reparametrization.…

Methodology · Statistics 2026-05-26 Issam-Ali Moindjié , Cédric Beaulac , Marie-Hélène Descary

This work studies the mean-square stability and stabilization problem for networked feedback systems. Data transmission delays in the network channels of the systems are considered. It is assumed that these delays are i.i.d. processes with…

Systems and Control · Electrical Eng. & Systems 2022-09-20 Jieying Lu , Junhui Li , Weizhou Su

In this paper, we focus on the tempered subdiffusive Black-Scholes model. The main part of our work consists of the finite difference method as a numerical approach to the option pricing in the considered model. We derive the governing…

Numerical Analysis · Mathematics 2022-05-16 Grzegorz Krzyżanowski , Marcin Magdziarz

Quantum Fisher information plays a central role in the field of quantum metrology. In this paper we study the problem of quantum Fisher information of unitary processes. Associated to each parameter $\theta_i$ of unitary process…

Quantum Physics · Physics 2018-11-15 Mohammad Javad Shemshadi , Seyed Javad Akhtarshenas

The averaged steady-state surprisal links a driven stochastic system's information processing to its nonequilibrium thermodynamic response. By explicitly accounting for the effects of nonequilibrium steady states, a decomposition of the…

Statistical Mechanics · Physics 2023-06-07 Mikhael T. Semaan , James P. Crutchfield

In this dissertation, an abstract formalism extending information geometry is introduced. This framework encompasses a broad range of modelling problems, including possible applications in machine learning and in the information theoretical…

Mathematical Physics · Physics 2015-01-06 Ben Anthonis

Hierarchical parametric models consisting of observable and latent variables are widely used for unsupervised learning tasks. For example, a mixture model is a representative hierarchical model for clustering. From the statistical point of…

Machine Learning · Statistics 2014-01-24 Keisuke Yamazaki

We provide series expansions for the tempered stable densities and for the price of European-style contracts in the exponential L\'evy model driven by the tempered stable process. These formulas recover several popular option pricing…

Computational Finance · Quantitative Finance 2025-10-03 Gaetano Agazzotti , Jean-Philippe Aguilar

We estimate the teleported and the gained parameters by means of Fisher information in a non-inertial frame. The sender and the receiver share an accelerated maximum or partial entangled state. The estimation degree of these parameters…

Quantum Physics · Physics 2017-03-27 N. Metwally

The importance of the quantum Fisher information metric is testified by the number of applications that this has in very different fields, ranging from hypothesis testing to metrology, passing through thermodynamics. Still, from the rich…

Quantum Physics · Physics 2024-04-30 Matteo Scandi , Paolo Abiuso , Jacopo Surace , Dario De Santis

Thermally activated magnetization decay is studied in ensembles of clusters of interacting dipolar moments by applying the master-equation formalism, as a model of thermal relaxation in systems of interacting single-domain ferromagnetic…

Statistical Mechanics · Physics 2014-05-27 O. Hovorka , J. Barker , G. Friedman , R. W. Chantrell

The modified biharmonic equation is encountered in a variety of application areas, including streamfunction formulations of the Navier-Stokes equations. We develop a separation of variables representation for this equation in polar…

Numerical Analysis · Mathematics 2017-10-17 Travis Askham

In order to analyze and extract different structural properties of distributions, one can introduce different coordinate systems over the manifold of distributions. In Evolutionary Computation, the Walsh bases and the Building Block Bases…

Adaptation and Self-Organizing Systems · Physics 2007-05-23 Marc Toussaint

We define a metric and a family of $\alpha$-connections in statistical manifolds, based on $\varphi$-divergence, which emerges in the framework of $\varphi$-families of probability distributions. This metric and $\alpha$-connections…

Probability · Mathematics 2015-11-05 Rui F. Vigelis , David C. de Souza , Charles C. Cavalcante

We investigate exponential stock models driven by tempered stable processes, which constitute a rich family of purely discontinuous L\'{e}vy processes. With a view of option pricing, we provide a systematic analysis of the existence of…

Mathematical Finance · Quantitative Finance 2025-11-21 Uwe Küchler , Stefan Tappe

We generalize stochastic thermodynamics to include information reservoirs. Such information reservoirs, which can be modeled as a sequence of bits, modify the second law. For example, work extraction from a system in contact with a single…

Statistical Mechanics · Physics 2014-11-17 Andre C. Barato , Udo Seifert

The quantum Fisher information represents the continuous family of metrics on the space of quantum states and places the fundamental limit on the accuracy of quantum state estimation. We show that the entire family of the quantum Fisher…

Quantum Physics · Physics 2023-06-07 Tomohiro Shitara , Masahito Ueda

Divergences are fundamental to the information criteria that underpin most signal processing algorithms. The alpha-beta family of divergences, designed for non-negative data, offers a versatile framework that parameterizes and continuously…

Machine Learning · Computer Science 2026-03-27 Sergio Cruces