43 citations · 73 across the 9 of their papers we have counts for
10 papers
Waves 2026 Book of Abstracts
Lise-Marie Imbert-Gerard, Chrysoula Tsogka, Daniel Appelo +4
WAVES 2026, 17th International Conference on Mathematical and Numerical Aspects of Wave Propagation Concordia University (John Molson Building), Montreal, Canada, June 22-26, 2026…
Multi-level Neural Networks for Accurate Solutions of Boundary-Value Problems
Ziad Aldirany, Régis Cottereau, Marc Laforest +1
The solution to partial differential equations using deep learning approaches has shown promising results for several classes of initial and boundary-value problems. However, their…
Operator approximation of the wave equation based on deep learning of Green's function
Ziad Aldirany, Régis Cottereau, Marc Laforest +1
Deep operator networks (DeepONets) have demonstrated their capability of approximating nonlinear operators for initial- and boundary-value problems. One attractive feature of DeepO…
Optimal Design of Validation Experiments for the Prediction of Quantities of Interest
Antonin Paquette-Rufiange, Serge Prudhomme, Marc Laforest
Numerical predictions of quantities of interest measured within physical systems rely on the use of mathematical models that should be validated, or at best, not invalidated. Model…
PGD reduced-order modeling for structural dynamics applications
Clément Vella, Serge Prudhomme
We propose in this paper a Proper Generalized Decomposition (PGD) approach for the solution of problems in linear elastodynamics. The novelty of the work lies in the development of…
Coupling approaches for classical linear elasticity and bond-based peridynamic models
Patrick Diehl, Serge Prudhomme
Local-nonlocal coupling approaches provide a means to combine the computational efficiency of local models and the accuracy of nonlocal models. This paper studies the continuous an…
On the treatment of boundary conditions for bond-based peridynamic models
Serge Prudhomme, Patrick Diehl
In this paper, we propose two approaches to apply boundary conditions for bond-based peridynamic models. There has been in recent years a renewed interest in the class of so-called…
Scheduling optimization of parallel linear algebra algorithms using Supervised Learning
G. Laberge, S. Shirzad, P. Diehl +3
Linear algebra algorithms are used widely in a variety of domains, e.g machine learning, numerical physics and video games graphics. For all these applications, loop-level parallel…
Probabilistic modeling and global sensitivity analysis for storage in geological formations: a spectral approach
Bilal Saad, Alen Alexanderian, Serge Prudhomme +1
This work focuses on the simulation of storage in deep underground formations under uncertainty and seeks to understand the impact of uncertainties in reservoir properties o…
Optimal Data Split Methodology for Model Validation
Rebecca Morrison, Corey Bryant, Gabriel Terejanu +2
The decision to incorporate cross-validation into validation processes of mathematical models raises an immediate question - how should one partition the data into calibration and…