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ORCIDDavid Ryckelynck
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2020 – today
- 2024
[b1]David Ryckelynck
, Fabien Casenave, Nissrine Akkari:
Manifold Learning - Model Reduction in Engineering. Springer Briefs in Computer Science, Springer 2024, ISBN 978-3-031-52766-1, pp. 1-107- [c4]Matteo Bastico, Etienne Decencière, Laurent Corté, Yannick Tillier, David Ryckelynck:
Coupled Laplacian Eigenmaps for Locally-Aware 3D Rigid Point Cloud Matching. CVPR 2024: 3447-3458 - [i11]Matteo Bastico, Etienne Decencière, Laurent Corté, Yannick Tillier, David Ryckelynck:
Coupled Laplacian Eigenmaps for Locally-Aware 3D Rigid Point Cloud Matching. CoRR abs/2402.17372 (2024) - 2023
- [j9]Hamza Boukraichi, Nissrine Akkari, Fabien Casenave, David Ryckelynck:
A priori compression of convolutional neural networks for wave simulators. Eng. Appl. Artif. Intell. 126: 106973 (2023) - [c3]Matteo Bastico, David Ryckelynck, Laurent Corté, Yannick Tillier, Etienne Decencière:
A Simple and Robust Framework for Cross-Modality Medical Image Segmentation applied to Vision Transformers. ICCV (Workshops) 2023: 4130-4140 - [i10]Hamza Boukraichi, Nissrine Akkari, Fabien Casenave, David Ryckelynck:
A priori compression of convolutional neural networks for wave simulators. CoRR abs/2304.04964 (2023) - [i9]Matteo Bastico, David Ryckelynck, Laurent Corté, Yannick Tillier, Etienne Decencière:
A Simple and Robust Framework for Cross-Modality Medical Image Segmentation applied to Vision Transformers. CoRR abs/2310.05572 (2023) - 2022
- [j8]Nissrine Akkari, Fabien Casenave, David Ryckelynck, Christian Rey:
An updated Gappy-POD to capture non-parameterized geometrical variation in fluid dynamics problems. Adv. Model. Simul. Eng. Sci. 9(1): 3 (2022) - [j7]Thomas Daniel, Fabien Casenave, Nissrine Akkari, Ali Ketata, David Ryckelynck:
Physics-informed cluster analysis and a priori efficiency criterion for the construction of local reduced-order bases. J. Comput. Phys. 458: 111120 (2022) - 2021
- [j6]Youssef Hammadi, David Ryckelynck, Amin El-Bakkali:
Data-driven reduced bond graph for nonlinear multiphysics dynamic systems. Appl. Math. Comput. 409: 126359 (2021) - [i8]Thomas Daniel, Fabien Casenave, Nissrine Akkari, David Ryckelynck:
Data augmentation and feature selection for automatic model recommendation in computational physics. CoRR abs/2101.04530 (2021) - [i7]Thomas Daniel, Ali Ketata, Fabien Casenave, David Ryckelynck:
Physics-informed cluster analysis and a priori efficiency criterion for the construction of local reduced-order bases. CoRR abs/2103.13683 (2021) - [i6]João P. C. Bertoldo, Etienne Decencière, David Ryckelynck, Henry Proudhon:
A modular U-Net for automated segmentation of X-ray tomography images in composite materials. CoRR abs/2107.07468 (2021) - [i5]Thomas Daniel, Fabien Casenave, Nissrine Akkari, David Ryckelynck, Christian Rey:
Uncertainty quantification for industrial design using dictionaries of reduced order models. CoRR abs/2108.04012 (2021) - [i4]Thomas Daniel, Fabien Casenave, Nissrine Akkari, David Ryckelynck:
Optimal piecewise linear data compression for solutions of parametrized partial differential equations. CoRR abs/2108.12291 (2021) - [i3]Hamza Boukraichi, Nissrine Akkari, Fabien Casenave, David Ryckelynck:
Uncertainty quantification in a mechanical submodel driven by a Wasserstein-GAN. CoRR abs/2110.13680 (2021) - 2020
- [j5]Thomas Daniel, Fabien Casenave, Nissrine Akkari, David Ryckelynck:
Model order reduction assisted by deep neural networks (ROM-net). Adv. Model. Simul. Eng. Sci. 7(1): 16 (2020) - [c2]Fabien Casenave, Nissrine Akkari, David Ryckelynck:
Reduced Order Modeling Assisted by Convolutional Neural Network for Thermal Problems with Nonparametrized Geometrical Variability. SAI (2) 2020: 245-263 - [c1]Nissrine Akkari, Fabien Casenave, Marc-Eric Perrin, David Ryckelynck:
Deep Convolutional Generative Adversarial Networks Applied to 2D Incompressible and Unsteady Fluid Flows. SAI (2) 2020: 264-276 - [i2]Youssef Hammadi, David Ryckelynck, Amin El-Bakkali:
Reduced Bond Graph via machine learning for nonlinear multiphysics dynamic systems. CoRR abs/2004.13971 (2020)
2010 – 2019
- 2018
- [j4]Franck Nguyen, Selim M. Barhli, Daniel Pino Muñoz, David Ryckelynck:
Computer Vision with Error Estimation for Reduced Order Modeling of Macroscopic Mechanical Tests. Complex. 2018: 3791543:1-3791543:10 (2018) - 2016
- [j3]David Ryckelynck, Djamel Missoum Benziane:
Hyper-reduction framework for model calibration in plasticity-induced fatigue. Adv. Model. Simul. Eng. Sci. 3(1): 15:1-15:16 (2016) - [i1]Felix Fritzen, Bernard Haasdonk, David Ryckelynck, Sebastian Schöps:
An algorithmic comparison of the Hyper-Reduction and the Discrete Empirical Interpolation Method for a nonlinear thermal problem. CoRR abs/1610.05029 (2016) - 2015
- [j2]David Ryckelynck, Laurent Gallimard, Samuel Jules:
Estimation of the validity domain of hyper-reduction approximations in generalized standard elastoviscoplasticity. Adv. Model. Simul. Eng. Sci. 2(1): 6:1-6:19 (2015) - 2011
- [j1]Cyrille Allery, Aziz Hamdouni, David Ryckelynck, N. Verdon:
A priori reduction method for solving the two-dimensional Burgers' equations. Appl. Math. Comput. 217(15): 6671-6679 (2011)
Coauthor Index
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