A Flexible Technique for Accurate Omnidirectional Camera Calibration and Structure from Motion

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Time-domain solutions of Maxwell’s equations in homogeneous and isotropic media are paramount to studying transient or broadband phenomena. However, analytical solutions are generally unavailable for practical applications, while numerical solutions are co ...

The conditional mean is a fundamental and important quantity whose applications include the theories of estimation and rate-distortion. It is also notoriously difficult to work with. This paper establishes novel bounds on the differential entropy of the co ...

This paper considers an additive Gaussian noise channel with arbitrarily distributed finite variance input signals. It studies the differential entropy of the minimum mean-square error (MMSE) estimator and provides a new lower bound which connects the diff ...

Eigendecomposition of symmetric matrices is at the heart of many computer vision algorithms. However, the derivatives of the eigenvectors tend to be numerically unstable, whether using the SVD to compute them analytically or using the Power Iteration (PI) ...

For lumped homogeneous reaction systems, this paper presents a kinetic model identification scheme that provides maximum-likelihood parameter estimates and guarantees convergence to global optimality. The use of the extent-based incremental approach allows ...

The investigation of spontaneous and evoked neuronal activity from functional Magnetic Resonance Imaging (fMRI) data has come to play a significant role in deepening our understanding of brain function. As this research trend continues, activity detection ...

In this paper we derive a series expansion for the price of a continuously sampled arithmetic Asian option in the Black-Scholes setting. The expansion is based on polynomials that are orthogonal with respect to the log-normal distribution. All terms in the ...

Omnidirectional (or 360-degree) images and videos are emergent signals in many areas such as robotics and virtual/augmented reality. In particular, for virtual reality, they allow an immersive experience in which the user is provided with a 360-degree fiel ...

Recent advances in statistical learning and convex optimization have inspired many successful practices. Standard theories assume smoothness---bounded gradient, Hessian, etc.--- and strong convexity of the loss function. Unfortunately, such conditions may ...

Short beams are the key building blocks in many compliant mechanisms. Hence, deriving a simple yet accurate model of their elastokinematics is an important issue. Since the Euler-Bernoulli beam theory fails to accurately model these beams, we use the Timos ...

The performance of the modulated-gradient subgrid-scale (SGS) model is investigated using large-eddy simulation (LES) of the neutral atmospheric boundary layer within the weather research and forecasting model. Since the model includes a finite-difference ...

This thesis presents new flexible dynamic stochastic models for the evolution of market prices and new methods for the valuation of derivatives. These models and methods build on the recently characterized class of polynomial jump-diffusion processes for w ...

The identification of reaction kinetics represents the main challenge in building models for reaction systems. The identification task can be performed via either simultaneous model identification (SMI) or incremental model identification (IMI), the latter ...

This thesis is devoted to the derivation of error estimates for partial differential equations with random input data, with a focus on a posteriori error estimates which are the basis for adaptive strategies. Such procedures aim at obtaining an approximati ...

This paper develops a method to compute any bosonic conformal block as a series expansion in the optimal radial coordinate introduced by Hogervorst and Rychkov. The method reduces to the known result when the external operators are all the same scalar oper ...

Small relative perturbations to the entries of an essentially nonnegative matrix introduce small relative errors to entries of its exponential. It is thus desirable to compute the exponential with high componentwise relative accuracy. Taylor series approxi ...

We study the single-phase flow in a saturated, bounded heterogeneous porous medium. We model the permeability as a log-normal random field. We perform a perturbation analysis, expanding the solution in Taylor series. The series is directly computable in th ...

A hybrid acceleration algorithm for the computation of the static potential Green’s functions of a rectangular cavity is proposed. Similarly to Ewald’s method, it combines the series expansions in terms of images and modes. The main particularity with resp ...

We provide here some probabilistic interpretations of the generalized binomial distributions proposed by Gazeau et al. ["Generating functions for generalized binomial distributions," J. Math. Phys. 53, 103304 (2012)]. In the second part, we prove the "stro ...

Based on Volterra series the work presents a novel local nonlinear model of a certain class of linear-analytic systems. The special form of the expressions for the Laplace-domain Volterra kernels of such systems is exploited to obtain an approximation stru ...

A Flexible Technique for Accurate Omnidirectional Camera Calibration and Structure from Motion

Chattez avec Graph Search

The time-domain Cartesian multipole expansion of electromagnetic fields

Differential Entropy of the Conditional Expectation Under Additive Gaussian Noise

Differential Entropy of the Conditional Expectation under Gaussian Noise

Robust Differentiable SVD

Maximum-likelihood estimation of kinetic parameters via the extent-based incremental approach

Bold Signal Deconvolution Under Uncertain HÆModynamics: A Semi-Blind Approach

Asian option pricing with orthogonal polynomials

Visual Distortions in 360-degree Videos

Learning without Smoothness and Strong Convexity

An Analytical Model for Beam Flexure Modules Based on Timoshenko Beam Theory

A Modulated-Gradient Parametrization for the Large-Eddy Simulation of the Atmospheric Boundary Layer Using the Weather Research and Forecasting Model

Polynomial models in finance

Global Identification of Kinetic Parameters via the Extent-based Incremental Approach

A posteriori error estimation for partial differential equations with random input data

Radial expansion for spinning conformal blocks

Aggressively Truncated Taylor Series Method For Accurate Computation Of Exponentials Of Essentially Nonnegative Matrices

Perturbation analysis for the Darcy problem with log-normal permeability

A Recursive Acceleration Technique for Static Potential Green's Functions of a Rectangular Cavity Combining Image and Modal Series

Proof of a conjecture by Gazeau et al. using the Gould-Hopper polynomials

A Local Nonlinear Model for the Approximation and Identification of a Class of Systems