Joël Chaskalovic

According to our database, Joël Chaskalovic authored at least 25 papers between 2008 and 2025.

Collaborative distances:

• Dijkstra number of five.
• Erdős number of five.

2025

A refined first-order expansion formula in Rn: Application to interpolation and finite element error estimates.

Joël Chaskalovic, Franck Assous

J. Comput. Appl. Math., 2025

Enhancing interpolation and approximation error estimates using a novel Taylor-like formula.

Joël Chaskalovic, Franck Assous

J. Comput. Appl. Math., 2025

2024

A new second order Taylor-like theorem with an optimized reduced remainder.

Joël Chaskalovic, Franck Assous, Hessam Jamshidipour

J. Comput. Appl. Math., March, 2024

2023

An optimal first-order Taylor-like formula with a minimized remainder.

Joël Chaskalovic, Franck Assous

CoRR, 2023

Improved P₁-interpolation error estimates in W^{1, p}(]0, 1[): Application to finite element method.

Joël Chaskalovic, Franck Assous

CoRR, 2023

A new second order Taylor-like theorem with an optimized reduced remainder.

Joël Chaskalovic, Franck Assous

CoRR, 2023

2022

A New First Order Expansion Formula with a Reduced Remainder.

Joël Chaskalovic, Hessam Jamshidipour

Axioms, 2022

Generalized Beta Prime Distribution Applied to Finite Element Error Approximation.

Joël Chaskalovic, Franck Assous

Axioms, 2022

2021

Numerical Validation of Probabilistic Laws to Evaluate finite element error estimates.

Joël Chaskalovic, Franck Assous

Math. Model. Anal., 2021

A New First Order Taylor-like Theorem With An Optimized Reduced Remainder.

Joël Chaskalovic, Hessam Jamshidipour

CoRR, 2021

A Probabilistic Approach for Solutions of Deterministic PDE's as Well as Their Finite Element Approximations.

Joël Chaskalovic

Axioms, 2021

2020

On generalized binomial laws to evaluate finite element accuracy: preliminary probabilistic results for adaptive mesh refinement.

Joël Chaskalovic, Franck Assous

J. Num. Math., 2020

A probabilistic approach for exact solutions of determinist PDE's as well as their finite element approximations.

Joël Chaskalovic

CoRR, 2020

A New Mixed Functional-probabilistic Approach for Finite Element Accuracy.

Joël Chaskalovic, Franck Assous

Comput. Methods Appl. Math., 2020

A New Probabilistic Interpretation of the Bramble-Hilbert Lemma.

Joël Chaskalovic, Franck Assous

Comput. Methods Appl. Math., 2020

2018

From a Geometrical Interpretation of Bramble-Hilbert Lemma to a Probability Distribution for Finite Element Accuracy.

Joël Chaskalovic, Franck Assous

Proceedings of the Finite Difference Methods. Theory and Applications, 2018

2017

Probabilistic Approach to characterize Quantitative uncertainty in numerical Approximations.

Joël Chaskalovic, Franck Assous

Math. Model. Anal., 2017

2016

Data mining and probabilistic models for error estimate analysis of finite element method.

Joël Chaskalovic, Franck Assous

Math. Comput. Simul., 2016

2015

Multi-objective analysis of computational models.

Stéphane Doncieux, Jean Liénard, Benoît Girard, Mohamed Hamdaoui, Joël Chaskalovic

CoRR, 2015

2014

Indeterminate constants in numerical approximations of PDEs: A pilot study using data mining techniques.

Franck Assous, Joël Chaskalovic

J. Comput. Appl. Math., 2014

A paraxial asymptotic model for the coupled Vlasov-Maxwell problem in electromagnetics.

Franck Assous, Joël Chaskalovic

J. Comput. Appl. Math., 2014

2011

Data Mining Methods For Performance Evaluations To Asymptotic Numerical Models.

Franck Assous, Joël Chaskalovic

Proceedings of the International Conference on Computational Science, 2011

Data mining techniques for scientific computing: Application to asymptotic paraxial approximations to model ultrarelativistic particles.

Franck Assous, Joël Chaskalovic

J. Comput. Phys., 2011

2010

On the algorithmic complexity of static structures.

Joel Ratsaby, Joël Chaskalovic

J. Syst. Sci. Complex., 2010

2008

Algorithmic complexity and randomness in elastic solids

Joel Ratsaby, Joël Chaskalovic

CoRR, 2008