Publications related to Generating Sparse Stochastic Processes Using Matched Splines

Stochastic partial differential equations driven by Lévy white noises

We study various aspects of stochastic partial differential equations driven by Lévy white noise. This driving noise, which is a generalization of Gaussian white noise, can be viewed either as a generalized random process or as an independently scattered r ...

EPFL2017

Methods of approximation influence aquatic ecosystem metabolism estimates

Janine Rüegg

Aquatic ecologists have recently employed dynamic models to estimate aquatic ecosystem metabolism. All approaches involve numerically solving a differential equation describing dissolved oxygen (DO) dynamics. Although the DO differential equation can be so ...

Association for the Sciences of Limnology and Oceanography2016

Hermite Snakes with Control of Tangents

Michaël Unser, Julien René Pierre Fageot, Virginie Sophie Uhlmann

We introduce a new model of parametric contours defined in a continuous fashion. Our curve model relies on Hermite spline interpolation and can easily generate curves with sharp discontinuities; it also grants direct access to the tangent at each location. ...

IEEE2016

Statistical Optimality of Hermite Splines

Michaël Unser, Julien René Pierre Fageot, Virginie Sophie Uhlmann, Harshit Gupta

Hermite splines are commonly used for interpolating data when samples of the derivative are available, in a scheme called Hermite interpolation. Assuming a suitable statistical model, we demonstrate that this method is actually optimal for reconstructing r ...

IEEE2015

Sampling and (Sparse) Stochastic Processes: A Tale of Splines and Innovation

Michaël Unser

The commonality between splines and Gaussian or sparse stochastic processes is that they are ruled by the same type of differential equations. Our purpose here is to demonstrate that this has profound implications for the three primary forms of sampling: u ...

IEEE2015

Max-stable processes and stationary systems of Levy particles

Sebastian Engelke

We study stationary max-stable processes {n(t): t is an element of R} admitting a representation of the form n(t) = max(i is an element of N) (U-i +Y-i(t)), where Sigma(infinity)(i=1) delta U-i is a Poisson point process on R with intensity e(-u)du, and Y1 ...

Elsevier2015

A Unified Formulation of Gaussian Versus Sparse Stochastic Processes-Part II: Discrete-Domain Theory

Michaël Unser, Arash Amini, Pouya Dehghani Tafti, Hagay Kirshner

This paper is devoted to the characterization of an extended family of continuous-time autoregressive moving average (CARMA) processes that are solutions of stochastic differential equations driven by white Levy innovations. These are completely specified ...

Ieee-Inst Electrical Electronics Engineers Inc2014

A Unified Formulation of Gaussian Versus Sparse Stochastic Processes-Part I: Continuous-Domain Theory

Michaël Unser, Pouya Dehghani Tafti

We introduce a general distributional framework that results in a unifying description and characterization of a rich variety of continuous-time stochastic processes. The cornerstone of our approach is an innovation model that is driven by some generalized ...

Ieee-Inst Electrical Electronics Engineers Inc2014

Invariant manifolds with boundary for jump-diffusions

Damir Filipovic

We provide necessary and sufficient conditions for stochastic invariance of finite dimensional submanifolds with boundary in Hilbert spaces for stochastic partial differential equations driven by Wiener processes and Poisson random measures. ...

Univ Washington, Dept Mathematics2014

Cardinal Hermite Exponential Splines: Theoretical Insights and Applications to Active Contours

Michaël Unser, Virginie Sophie Uhlmann

Cardinal Hermite exponential spline functions are a generalization of the classical cardinal Hermite polynomial splines. In this work we consider the 4-dimensional space

ε _{ 4 }

= {1, x,

e ^{ \alpha x }

,

e ^{ -\alpha x }

} with α ∈ $ ℝ ^{ + } ...

SMAI-SIGMA2014

Generating Sparse Stochastic Processes Using Matched Splines

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Stochastic partial differential equations driven by Lévy white noises

Methods of approximation influence aquatic ecosystem metabolism estimates

Hermite Snakes with Control of Tangents

Statistical Optimality of Hermite Splines

Sampling and (Sparse) Stochastic Processes: A Tale of Splines and Innovation

Max-stable processes and stationary systems of Levy particles

A Unified Formulation of Gaussian Versus Sparse Stochastic Processes-Part II: Discrete-Domain Theory

A Unified Formulation of Gaussian Versus Sparse Stochastic Processes-Part I: Continuous-Domain Theory

Invariant manifolds with boundary for jump-diffusions

Cardinal Hermite Exponential Splines: Theoretical Insights and Applications to Active Contours

Stochastic partial differential equations driven by Lévy white noises

Hermite Snakes with Control of Tangents

Statistical Optimality of Hermite Splines

Methods of approximation influence aquatic ecosystem metabolism estimates

Sampling and (Sparse) Stochastic Processes: A Tale of Splines and Innovation

Cardinal Hermite Exponential Splines: Theoretical Insights and Applications to Active Contours

Max-stable processes and stationary systems of Levy particles

A Unified Formulation of Gaussian Versus Sparse Stochastic Processes-Part I: Continuous-Domain Theory

Invariant manifolds with boundary for jump-diffusions

A Unified Formulation of Gaussian Versus Sparse Stochastic Processes-Part II: Discrete-Domain Theory