David Ryckelynck

28 papers A* 1Journal 23Unranked 3

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	Functional maps regularization for high quality mesh morphing applied to shape registration in computed tomography. Eng. Comput. Amelia Ferhat, Henry Proudhon, Clement Remacha, David Ryckelynck
2026	J	`jnl`	LmPT: Conditional Point Transformer for Anatomical Landmark Detection on 3D Point Clouds. CoRR Matteo Bastico, Pierre Onghena, David Ryckelynck, Beatriz Marcotegui, Santiago Velasco-Forero, Laurent Corté, Caroline Robine-Decourcelle, Etienne Decencière
2025	J	`jnl`	Rethinking Metrics and Diffusion Architecture for 3D Point Cloud Generation. CoRR Matteo Bastico, David Ryckelynck, Laurent Corté, Yannick Tillier, Etienne Decencière
2024	A*	`conf`	Coupled Laplacian Eigenmaps for Locally-Aware 3D Rigid Point Cloud Matching. CVPR Matteo Bastico, Etienne Decencière, Laurent Corté, Yannick Tillier, David Ryckelynck
2024	J	`jnl`	Coupled Laplacian Eigenmaps for Locally-Aware 3D Rigid Point Cloud Matching. CoRR Matteo Bastico, Etienne Decencière, Laurent Corté, Yannick Tillier, David Ryckelynck
2024	—	`book`	Manifold Learning - Model Reduction in Engineering David Ryckelynck, Fabien Casenave, Nissrine Akkari
2023	—	`conf`	A Simple and Robust Framework for Cross-Modality Medical Image Segmentation applied to Vision Transformers. ICCV (Workshops) Matteo Bastico, David Ryckelynck, Laurent Corté, Yannick Tillier, Etienne Decencière
2023	J	`jnl`	A Simple and Robust Framework for Cross-Modality Medical Image Segmentation applied to Vision Transformers. CoRR Matteo Bastico, David Ryckelynck, Laurent Corté, Yannick Tillier, Etienne Decencière
2023	J	`jnl`	A priori compression of convolutional neural networks for wave simulators. CoRR Hamza Boukraichi, Nissrine Akkari, Fabien Casenave, David Ryckelynck
2023	J	`jnl`	A priori compression of convolutional neural networks for wave simulators. Eng. Appl. Artif. Intell. Hamza Boukraichi, Nissrine Akkari, Fabien Casenave, David Ryckelynck
2022	J	`jnl`	An updated Gappy-POD to capture non-parameterized geometrical variation in fluid dynamics problems. Adv. Model. Simul. Eng. Sci. Nissrine Akkari, Fabien Casenave, David Ryckelynck, Christian Rey
2022	J	`jnl`	Physics-informed cluster analysis and a priori efficiency criterion for the construction of local reduced-order bases. J. Comput. Phys. Thomas Daniel, Fabien Casenave, Nissrine Akkari, Ali Ketata, David Ryckelynck
2021	J	`jnl`	A modular U-Net for automated segmentation of X-ray tomography images in composite materials. CoRR João P. C. Bertoldo, Etienne Decencière, David Ryckelynck, Henry Proudhon
2021	J	`jnl`	Data augmentation and feature selection for automatic model recommendation in computational physics. CoRR Thomas Daniel, Fabien Casenave, Nissrine Akkari, David Ryckelynck
2021	J	`jnl`	Data-driven reduced bond graph for nonlinear multiphysics dynamic systems. Appl. Math. Comput. Youssef Hammadi, David Ryckelynck, Amin El-Bakkali
2021	J	`jnl`	Optimal piecewise linear data compression for solutions of parametrized partial differential equations. CoRR Thomas Daniel, Fabien Casenave, Nissrine Akkari, David Ryckelynck
2021	J	`jnl`	Physics-informed cluster analysis and a priori efficiency criterion for the construction of local reduced-order bases. CoRR Thomas Daniel, Ali Ketata, Fabien Casenave, David Ryckelynck
2021	J	`jnl`	Uncertainty quantification for industrial design using dictionaries of reduced order models. CoRR Thomas Daniel, Fabien Casenave, Nissrine Akkari, David Ryckelynck, Christian Rey
2021	J	`jnl`	Uncertainty quantification in a mechanical submodel driven by a Wasserstein-GAN. CoRR Hamza Boukraichi, Nissrine Akkari, Fabien Casenave, David Ryckelynck
2020	—	`conf`	Deep Convolutional Generative Adversarial Networks Applied to 2D Incompressible and Unsteady Fluid Flows. SAI (2) Nissrine Akkari, Fabien Casenave, Marc-Eric Perrin, David Ryckelynck
2020	J	`jnl`	Model order reduction assisted by deep neural networks (ROM-net). Adv. Model. Simul. Eng. Sci. Thomas Daniel, Fabien Casenave, Nissrine Akkari, David Ryckelynck
2020	J	`jnl`	Reduced Bond Graph via machine learning for nonlinear multiphysics dynamic systems. CoRR Youssef Hammadi, David Ryckelynck, Amin El-Bakkali
2020	—	`conf`	Reduced Order Modeling Assisted by Convolutional Neural Network for Thermal Problems with Nonparametrized Geometrical Variability. SAI (2) Fabien Casenave, Nissrine Akkari, David Ryckelynck
2018	J	`jnl`	Computer Vision with Error Estimation for Reduced Order Modeling of Macroscopic Mechanical Tests. Complex. Franck Nguyen, Selim M. Barhli, Daniel Pino Muñoz, David Ryckelynck
2016	J	`jnl`	An algorithmic comparison of the Hyper-Reduction and the Discrete Empirical Interpolation Method for a nonlinear thermal problem. CoRR Felix Fritzen, Bernard Haasdonk, David Ryckelynck, Sebastian Schöps
2016	J	`jnl`	Hyper-reduction framework for model calibration in plasticity-induced fatigue. Adv. Model. Simul. Eng. Sci. David Ryckelynck, Djamel Missoum Benziane
2015	J	`jnl`	Estimation of the validity domain of hyper-reduction approximations in generalized standard elastoviscoplasticity. Adv. Model. Simul. Eng. Sci. David Ryckelynck, Laurent Gallimard, Samuel Jules
2011	J	`jnl`	A priori reduction method for solving the two-dimensional Burgers' equations. Appl. Math. Comput. Cyrille Allery, Aziz Hamdouni, David Ryckelynck, N. Verdon