activity
20182022
most citedTaylor-series expansion based numerical methods: a primer, performance benchmarking and new approaches for problems with non-smooth solutions

36 citations · 41 across the 4 of their papers we have counts for

collaborators

5 papers

math.NA2022

Smart cloud collocation: geometry-aware adaptivity directly from CAD

Thibault Jacquemin, Pratik Suchde, Stéphane P. A. Bordas

Computer Aided Design (CAD) is widely used in the creation and optimization of various industrial systems and processes. Transforming a CAD geometry into a computational discretiza…

cs.LG20212 cited

Machine learning in the social and health sciences

Anja K. Leist, Matthias Klee, Jung Hyun Kim +4

The uptake of machine learning (ML) approaches in the social and health sciences has been rather slow, and research using ML for social and health research questions remains fragme…

cs.CE20213 cited

Inverse deformation analysis: an experimental and numerical assessment using the FEniCS Project

Arnaud Mazier, Alexandre Bilger, Antonio E. Forte +25

In this paper, we develop a framework for solving inverse deformation problems using the FEniCS Project finite element software. We validate our approach with experimental imaging…

math.NA202036 cited

Taylor-series expansion based numerical methods: a primer, performance benchmarking and new approaches for problems with non-smooth solutions

Thibault Jacquemin, Satyendra Tomar, Konstantinos Agathos +2

We provide a primer to numerical methods based on Taylor series expansions such as generalized finite difference methods and collocation methods. We provide a detailed benchmarking…

cs.CE2018

Quantifying discretization errors for soft-tissue simulation in computer assisted surgery: a preliminary study

Michel Duprez, Stéphane P. A. Bordas, Marek Bucki +7

Errors in biomechanics simulations arise from modeling and discretization. Modeling errors are due to the choice of the mathematical model whilst discretization errors measure the…