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This paper presents a method that improve state-of-the-art of the concave point detection methods as a first step to segment overlapping objects on images. It is based on the analysis of the curvature of the objects contour. The method has…

Computer Vision and Pattern Recognition · Computer Science 2022-01-11 Miquel Miró-Nicolau , Biel Moyà-Alcover , Manuel Gonzàlez-Hidalgo , Antoni Jaume-i-Capó

Physical transformations are described by linear maps that are completely positive and trace preserving (CPTP). However, maps that are positive (P) but not completely positive (CP) are instrumental to derive separability/entanglement…

Quantum Physics · Physics 2023-01-10 Maciej Lewenstein , Guillem Müller-Rigat , Jordi Tura , Anna Sanpera

We consider the problem of graph estimation in a zero-inflated Gaussian model. In this model, zero-inflation is obtained by double truncation (right and left) of a Gaussian vector. The goal is to recover the latent graph structure of the…

Statistics Theory · Mathematics 2019-11-19 Gégout-Petit Anne , Gueudin-Muller Aurélie , Karmann Clémence

We present a quantitative statistical test for the presence of a crossover c0 in the Gutenberg-Richter distribution of earthquake seismic moments, separating the usual power law regime for seismic moments less than c0 from another faster…

Statistical Mechanics · Physics 2009-11-07 V. F. Pisarenko , D. Sornette

We show bifurcation of localized spike solutions from spatially constant states in systems of nonlocally coupled equations in the whole space. The main assumptions are a generic bifurcation of saddle-node or transcritical type for spatially…

Dynamical Systems · Mathematics 2017-05-02 Arnd Scheel , Tianyu Tao

Based on the Scale-Splitting (SCSP) iteration method presented by Hezari et al. in (A new iterative method for solving a class of complex symmetric system linear of equations, Numerical Algorithms 73 (2016) 927-955), we present a new…

Numerical Analysis · Mathematics 2017-10-09 Davod Khojasteh Salkuyeh

Dual descent methods are commonly used to solve network optimization problems because their implementation can be distributed through the network. However, their convergence rates are typically very slow. This paper introduces a family of…

Optimization and Control · Mathematics 2011-04-07 M. Zargham , A. Ribeiro , A. Jadbabaie , A. Ozdaglar

Normals with unknown parameters (NUP) can be used to convert nontrivial model-based estimation problems into iterations of linear least-squares or Gaussian estimation problems. In this paper, we extend this approach by augmenting factor…

Machine Learning · Statistics 2025-04-24 Yun-Peng Li , Hans-Andrea Loeliger

Sergey Pinchuk discovered a class of pairs of real polynomials in two variables that have a nowhere vanishing Jacobian determinant and define maps of the real plane to itself that are not one-to-one. This paper describes the asymptotic…

Algebraic Geometry · Mathematics 2009-09-25 L. Andrew Campbell

In this paper we present a theorem concerning an equivalent statement of the Jacobian Conjecture in terms of Picard-Vessiot extensions. Our theorem completes the earlier work of T. Crespo and Z. Hajto which suggested an effective criterion…

Commutative Algebra · Mathematics 2015-06-05 Elzbieta Adamus , Pawel Bogdan , Zbigniew Hajto

Computational modeling of pattern formation in nonequilibrium systems is a fundamental tool for studying complex phenomena in biology, chemistry, materials science and engineering. The pursuit for theoretical descriptions of some among…

Pattern Formation and Solitons · Physics 2022-02-08 D. L. Coelho , E. Vitral , J. Pontes , N. Mangiavacchi

Gaussian graphical models are widely used to infer dependence structures. Bayesian methods are appealing to quantify uncertainty associated with structural learning, i.e., the plausibility of conditional independence statements given the…

Methodology · Statistics 2025-11-05 Deborah Sulem , Jack Jewson , David Rossell

Quantum circuit cutting has emerged as a promising method for simulating large quantum circuits using a collection of small quantum machines. Running low-qubit "circuit fragments" not only overcomes the size limitation of near-term…

We confirm a long-standing conjecture concerning shear-induced chaos in stochastically perturbed systems exhibiting a Hopf bifurcation. The method of showing the main chaotic property, a positive Lyapunov exponent, is a computer-assisted…

Dynamical Systems · Mathematics 2023-10-26 Maxime Breden , Maximilian Engel

The Ohta-Kawasaki model for diblock copolymers exhibits a rich equilibrium bifurcation structure. Even on one-dimensional base domains the bifurcation set is characterized by high levels of multi-stability and numerous secondary bifurcation…

Dynamical Systems · Mathematics 2023-12-29 Peter Rizzi , Evelyn Sander , Thomas Wanner

Inferring unknown conic sections on the basis of noisy data is a challenging problem with applications in computer vision. A major limitation of the currently available methods for conic sections is that estimation methods rely on the…

Methodology · Statistics 2020-03-05 Subharup Guha , Sujit K. Ghosh

In this article, we prove the convergence of a semi-discrete numerical method applied to a general class of nonlocal nonlinear wave equations where the nonlocality is introduced through the convolution operator in space. The most important…

Numerical Analysis · Mathematics 2020-08-04 H. A. Erbay , S. Erbay , A. Erkip

We propose an approximation of nonlinear renewal equations by means of ordinary differential equations. We consider the integrated state, which is absolutely continuous and satisfies a delay differential equation. By applying the…

Numerical Analysis · Mathematics 2021-03-23 Francesca Scarabel , Odo Diekmann , Rossana Vermiglio

In this paper we generalize the technique of deflation to define two new methods to systematically find many local minima of a nonlinear least squares problem. The methods are based on the Gauss-Newton algorithm, and as such do not require…

Numerical Analysis · Mathematics 2025-06-13 Alban Bloor Riley , Marcus Webb , Michael L Baker

We study the problem of detecting change points (CPs) that are characterized by a subset of dimensions in a multi-dimensional sequence. A method for detecting those CPs can be formulated as a two-stage method: one for selecting relevant…

Machine Learning · Statistics 2018-03-05 Yuta Umezu , Ichiro Takeuchi
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