A5001182701- Advanced Numerical Analysis Techniques
- Numerical methods in engineering
- Advanced Numerical Methods in Computational Mathematics
- Electromagnetic Scattering and Analysis
- Image and Signal Denoising Methods
- Medical Image Segmentation Techniques
- Model Reduction and Neural Networks
- Numerical methods in inverse problems
- Electromagnetic Simulation and Numerical Methods
- Mathematical and Theoretical Epidemiology and Ecology Models
- Matrix Theory and Algorithms
- Image and Object Detection Techniques
- Advanced Graph Neural Networks
- Mathematical Biology Tumor Growth
- Ethics and Social Impacts of AI
- Numerical methods for differential equations
- Legal and Labor Studies
- Quantum chaos and dynamical systems
- Seismic Imaging and Inversion Techniques
- Evolution and Genetic Dynamics
- Mathematical Analysis and Transform Methods
- Advanced Multi-Objective Optimization Algorithms
- Computational Geometry and Mesh Generation
- European Criminal Justice and Data Protection
- Mathematical Approximation and Integration
Collegio Carlo Alberto
2015-2024
University of Turin
2014-2024
Istituto Nazionale di Alta Matematica Francesco Severi
2022-2024
University of Naples Federico II
2021-2023
University of Padua
2016
Innsbruck Medical University
2010
Epatocentro Ticino
2010
We construct cubature methods on scattered data via resampling the support of known algebraic formulas, by different kinds adaptive interpolation (polynomial, RBF, PUM). This approach gives a promising alternative to other recent methods, such as direct meshless RBF or least-squares formulas.
This paper explores the utilization of randomized SVD (rSVD) in context kernel matrices arising from radial basis functions (RBFs) for purpose solving interpolation and Poisson problems. We propose a truncated version rSVD, called trSVD, which yields stable solution with reduced condition number comparison to non-truncated variant, particularly when manipulating scale or shape parameter RBFs. Notably, trSVD exhibits exceptional proficiency capturing most significant singular values, enabling...
In this paper we propose a fast algorithm for trivariate interpolation, which is based on the partition of unity method constructing global interpolant by blending local radial basis function interpolants and using locally supported weight functions. The efficiently implemented optimized connecting with an effective cube-partition searching procedure. More precisely, construct cube structure, partitions domain strictly depends size its subdomains, so that new procedure and, accordingly,...
In this paper we propose a fast algorithm for bivariate interpolation of large scattered data sets. It is based on the partition unity method constructing global interpolant by blending radial basis functions as local approximants and using locally supported weight functions. The efficiently implemented optimized connecting with an effective cell-based searching procedure. More precisely, construct cell structure, which partitions domain strictly depends dimension subdomains, thus providing...
In this paper we present a new fast and accurate method for Radial Basis Function (RBF) approximation, including interpolation as special case, which enables us to effectively find the optimal value of RBF shape parameter. particular, propose statistical technique, called Bayesian optimization, that consists in modelling error function with Gaussian process, by which, through an iterative parameter is selected. The process step self-updated resulting relevant decrease search time respect...
A class of spline functions, called Lobachevsky splines, is proposed for landmark‐based image registration. Analytic expressions splines and some their properties are given, reasoning in the context probability theory. Because these functions have simple analytic compact support, transformations can be advantageously defined using them. Numerical results point out accuracy stability comparing them with Gaussians thin plate splines. Moreover, an application to a real‐life case (cervical X‐ray...
In dynamical systems saddle points partition the domain into basins of attractions remaining locally stable equilibria. This situation is rather common especially in population dynamics models, like prey–predator or competition systems. Focusing on squirrels models with niche, this paper we design algorithms for detection and refinement lying separatrix manifold partitioning phase space. We consider both two populations three cases. To reconstruct curve surface, apply Partition Unity method,...