David Ryckelynck

According to our database, David Ryckelynck authored at least 22 papers between 2011 and 2024.

Collaborative distances:

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

2024

Manifold Learning - Model Reduction in Engineering

David Ryckelynck, Fabien Casenave, Nissrine Akkari

Springer Briefs in Computer Science, Springer, ISBN: 978-3-031-52766-1, 2024

Coupled Laplacian Eigenmaps for Locally-Aware 3D Rigid Point Cloud Matching.

Matteo Bastico, Etienne Decencière, Laurent Corté, Yannick Tillier, David Ryckelynck

CoRR, 2024

2023

A priori compression of convolutional neural networks for wave simulators.

Hamza Boukraichi, Nissrine Akkari, Fabien Casenave, David Ryckelynck

CoRR, 2023

A Simple and Robust Framework for Cross-Modality Medical Image Segmentation applied to Vision Transformers.

Matteo Bastico, David Ryckelynck, Laurent Corté, Yannick Tillier, Etienne Decencière

Proceedings of the IEEE/CVF International Conference on Computer Vision, 2023

2022

Physics-informed cluster analysis and a priori efficiency criterion for the construction of local reduced-order bases.

Thomas Daniel, Fabien Casenave, Nissrine Akkari, Ali Ketata, David Ryckelynck

J. Comput. Phys., 2022

An updated Gappy-POD to capture non-parameterized geometrical variation in fluid dynamics problems.

Nissrine Akkari, Fabien Casenave, David Ryckelynck, Christian Rey

Adv. Model. Simul. Eng. Sci., 2022

2021

Uncertainty quantification in a mechanical submodel driven by a Wasserstein-GAN.

Hamza Boukraichi, Nissrine Akkari, Fabien Casenave, David Ryckelynck

CoRR, 2021

Optimal piecewise linear data compression for solutions of parametrized partial differential equations.

Thomas Daniel, Fabien Casenave, Nissrine Akkari, David Ryckelynck

CoRR, 2021

Uncertainty quantification for industrial design using dictionaries of reduced order models.

Thomas Daniel, Fabien Casenave, Nissrine Akkari, David Ryckelynck, Christian Rey

CoRR, 2021

A modular U-Net for automated segmentation of X-ray tomography images in composite materials.

João P. C. Bertoldo, Etienne Decencière, David Ryckelynck, Henry Proudhon

CoRR, 2021

Physics-informed cluster analysis and a priori efficiency criterion for the construction of local reduced-order bases.

Thomas Daniel, Ali Ketata, Fabien Casenave, David Ryckelynck

CoRR, 2021

Data augmentation and feature selection for automatic model recommendation in computational physics.

Thomas Daniel, Fabien Casenave, Nissrine Akkari, David Ryckelynck

CoRR, 2021

Data-driven reduced bond graph for nonlinear multiphysics dynamic systems.

Youssef Hammadi, David Ryckelynck, Amin El-Bakkali

Appl. Math. Comput., 2021

2020

Reduced Bond Graph via machine learning for nonlinear multiphysics dynamic systems.

Youssef Hammadi, David Ryckelynck, Amin El-Bakkali

CoRR, 2020

Model order reduction assisted by deep neural networks (ROM-net).

Thomas Daniel, Fabien Casenave, Nissrine Akkari, David Ryckelynck

Adv. Model. Simul. Eng. Sci., 2020

Reduced Order Modeling Assisted by Convolutional Neural Network for Thermal Problems with Nonparametrized Geometrical Variability.

Fabien Casenave, Nissrine Akkari, David Ryckelynck

Proceedings of the Intelligent Computing, 2020

Deep Convolutional Generative Adversarial Networks Applied to 2D Incompressible and Unsteady Fluid Flows.

Nissrine Akkari, Fabien Casenave, Marc-Eric Perrin, David Ryckelynck

Proceedings of the Intelligent Computing, 2020

2018

Computer Vision with Error Estimation for Reduced Order Modeling of Macroscopic Mechanical Tests.

Franck Nguyen, Selim M. Barhli, Daniel Pino Muñoz, David Ryckelynck

Complex., 2018

2016

An algorithmic comparison of the Hyper-Reduction and the Discrete Empirical Interpolation Method for a nonlinear thermal problem.

Felix Fritzen, Bernard Haasdonk, David Ryckelynck, Sebastian Schöps

CoRR, 2016

Hyper-reduction framework for model calibration in plasticity-induced fatigue.

David Ryckelynck, Djamel Missoum Benziane

Adv. Model. Simul. Eng. Sci., 2016

2015

Estimation of the validity domain of hyper-reduction approximations in generalized standard elastoviscoplasticity.

David Ryckelynck, Laurent Gallimard, Samuel Jules

Adv. Model. Simul. Eng. Sci., 2015

2011

A priori reduction method for solving the two-dimensional Burgers' equations.

Cyrille Allery, Aziz Hamdouni, David Ryckelynck, N. Verdon

Appl. Math. Comput., 2011