2 citations · 2 across the 11 of their papers we have counts for
12 papers
A plausible Parametrization of Modal Basis for Dynamical Systems Analysis
Sebastian Rodriguez, Sergio Torregrosa, Alicia Cordero +3
In the field of solid dynamics, knowing the corresponding modal basis of the system is capital, in order to improve design with respect to a desired dynamical behavior, such as avo…
Stress-constrained Topology Optimization for Metamaterial Microstructure Design
Yanda Chen, Sebastian Rodriguez, Beatriz Moya +1
Although stress-constrained topology optimization has been extensively studied in structural design, the development of optimization frameworks to enable the creation of metamateri…
M-Tensor Formalism: A Non-iterative High Dimensional Least Squares Regression for Nonlinear Models with Scarce Data
Remi Cloarec, Sebastian Rodriguez, Xavier Kestelyn +1
We present a multilinear regression framework based on tensor algebra tailored to high-dimensional contexts where data is scarce. We exploit algebraic properties of a partial tenso…
Rank Reduction AutoEncoders for Mechanical Design: Advancing Novel and Efficient Data-Driven Topology Optimization
Ismael Ben-Yelun, Mohammed El Fallaki Idrissi, Jad Mounayer +2
This work presents a data-driven framework for fast forward and inverse analysis in topology optimization (TO) by combining Rank Reduction Autoencoders (RRAEs) with neural latent-s…
Generative Parametric Design (GPD): A framework for real-time geometry generation and on-the-fly multiparametric approximation
Mohammed El Fallaki Idrissi, Jad Mounayer, Sebastian Rodriguez +2
This paper presents a novel paradigm in simulation-based engineering sciences by introducing a new framework called Generative Parametric Design (GPD). The GPD framework enables th…
RRAEDy: Adaptive Latent Linearization of Nonlinear Dynamical Systems
Jad Mounayer, Sebastian Rodriguez, Jerome Tomezyk +2
Most existing latent-space models for dynamical systems require fixing the latent dimension in advance, they rely on complex loss balancing to approximate linear dynamics, and they…
Bridging Data and Physics: A Graph Neural Network-Based Hybrid Twin Framework
M. Gorpinich, B. Moya, S. Rodriguez +6
Simulating complex unsteady physical phenomena relies on detailed mathematical models, simulated for instance by using the Finite Element Method (FEM). However, these models often…
Application of Reduced-Order Models for Temporal Multiscale Representations in the Prediction of Dynamical Systems
Elias Al Ghazal, Jad Mounayer, Beatriz Moya +3
Modeling and predicting the dynamics of complex multiscale systems remains a significant challenge due to their inherent nonlinearities and sensitivity to initial conditions, as we…
Quantum Potato Chips
Nikolay Murzin, Bruno Tenorio, Sebastian Rodriguez +2
We examine qubit states under symmetric informationally-complete measurements, representing state vectors as probability 4-vectors within a 3-simplex in . Using geometric…
The LATIN-PGD methodology to nonlinear dynamics and quasi-brittle materials for future earthquake engineering applications
Sebastian Rodriguez, Pierre-Etienne Charbonnel, Pierre Ladevèze +1
This paper presents a first implementation of the LArge Time INcrement (LATIN) method along with the model reduction technique called Proper Generalized Decomposition (PGD) for sol…
Rank Reduction Autoencoders
Jad Mounayer, Sebastian Rodriguez, Chady Ghnatios +2
The choice of an appropriate bottleneck dimension and the application of effective regularization are both essential for Autoencoders to learn meaningful representations from unlab…
Hyperharmonic analysis for the study of high-order information-theoretic signals
Anibal M. Medina-Mardones, Fernando E. Rosas, Sebastián E. Rodríguez +1
Network representations often cannot fully account for the structural richness of complex systems spanning multiple levels of organisation. Recently proposed high-order information…