D. González

发表

Recent advances on the use of separated representations

F. Chinesta, E. Cueto, A. Ammar, 2009 .

Non incremental strategies based on separated representations: applications in computational rheology

Elías Cueto, Francisco Chinesta, David González, 2010 .

Model order reduction in hyperelasticity: a proper generalized decomposition approach

Siamak Niroomandi, Icíar Alfaro, Elías Cueto, 2013 .

A comparative study on the performance of meshless approximations and their integration

Elías Cueto, David González, W. Quak, 2011 .

A Manifold Learning Approach for Integrated Computational Materials Engineering

E. Lopez, E. Abisset-Chavanne, F. Chinesta, 2017 .

Towards Simulated Reality

E. Cueto, D. González, I. Alfaro, 2019 .

Streamline upwind/Petrov–Galerkin‐based stabilization of proper generalized decompositions for high‐dimensional advection–diffusion equations

Pedro Díez, Antonio Huerta, Elías Cueto, 2013 .

Towards an Integrated NEM-Model Reduction Lagrangian Strategy in Fluid-Structure Interaction

David González, Elías Cueto, David Ryckelynck, 2005 .

Application of a Technique of Separation of Variables to the Numerical Simulation of Electrophysiology

Francisco Chinesta, David González, Elías Cueto, 2008 .

Recent advances in the meshless simulation of aluminium extrusion and other related forming processes

M. Doblaré, F. Chinesta, E. Cueto, 2006 .

Physically sound, self-learning digital twins for sloshing fluids

F. Chinesta, E. Cueto, D. González, 2020, PloS one.

Structure-preserving neural networks pdf

David Gonzalez, Francisco Chinesta, Quercus Hernandez, 2020, J. Comput. Phys..

Scientific Machine Learning for Coarse-Grained Constitutive Models

David González, Francisco Chinesta, Elías Cueto, 2020 .

Towards an Isogeometric Meshless Natural Element Method

M. Doblaré, E. Cueto, D. González, 2009 .

The α-shape Based Natural Element Method in Solid and Fluid Mechanics

M. Doblaré, F. Chinesta, E. Cueto, 2005 .

Data-driven correction of models for deformable solids

F. Chinesta, E. Cueto, D. González, 2019, PROCEEDINGS OF THE 22ND INTERNATIONAL ESAFORM CONFERENCE ON MATERIAL FORMING: ESAFORM 2019.

An Introduction to Structural Mechanics for Architects

Elías Cueto, David González, E. Cueto, 2018 .

A thermodynamics-informed active learning approach to perception and reasoning about fluids

F. Chinesta, E. Cueto, D. González, 2022, Computational Mechanics.

Thermodynamically consistent data-driven computational mechanics

F. Chinesta, E. Cueto, D. González, 2018, Continuum Mechanics and Thermodynamics.

L G ] 1 6 O ct 2 02 0 S TRUCTURE-PRESERVING NEURAL NETWORKS

F. Chinesta, E. Cueto, D. González, 2022 .

Hybrid constitutive modeling: data-driven learning of corrections to plasticity models

F. Chinesta, E. Cueto, J. Duval, 2018, International Journal of Material Forming.

Structure-preserving neural networks

Francisco Chinesta, Quercus Hernandez, Alberto Badias, 2020, Journal of Computational Physics.

Hybrid constitutive modeling: data-driven learning of corrections to plasticity models

Francisco Chinesta, Emmanuelle Abisset-Chavanne, David González, 2018, International Journal of Material Forming.

A higher order method based on local maximum entropy approximation

Elías Cueto, Manuel Doblaré, David González, 2010 .

Higher‐order natural element methods: Towards an isogeometric meshless method

Elías Cueto, Manuel Doblaré, David González, 2008 .

A natural neighbour Lagrange–Galerkin method for the simulation of Newtonian and Oldroyd‐B free surface flows

Elías Cueto, David González, Andrés Galavís, 2012 .

A natural element updated Lagrangian strategy for free-surface fluid dynamics

Elías Cueto, Francisco Chinesta, Manuel Doblaré, 2007, J. Comput. Phys..

A natural element updated Lagrangian approach for modelling fluid structure interactions

Elías Cueto, Francisco Chinesta, Manuel Doblaré, 2007 .

A PGD-based multiscale formulation for non-linear solid mechanics under small deformations

Manuel Doblaré, David González, J. A. Sanz-Herrera, 2016 .

FE2 multiscale in linear elasticity based on parametrized microscale models using proper generalized decomposition

M. Doblaré, D. González, A. Chico, 2013 .

Computational Patient Avatars for Surgery Planning

F. Chinesta, E. Cueto, D. González, 2015, Annals of Biomedical Engineering.

Model order reduction for real-time data assimilation through Extended Kalman Filters

Francisco Chinesta, Icíar Alfaro, Elías Cueto, 2017 .

Real‐time direct integration of reduced solid dynamics equations

David González, Elías Cueto, Francisco Chinesta, 2014 .

Thermodynamically consistent data-driven computational mechanics

David González, Elías Cueto, Francisco Chinesta, 2018, Continuum Mechanics and Thermodynamics.

Reduced order modeling for physically-based augmented reality

Icíar Alfaro, Francisco Chinesta, Alberto Badías, 2018, Computer Methods in Applied Mechanics and Engineering.

A Multidimensional Data-Driven Sparse Identification Technique: The Sparse Proper Generalized Decomposition

Francisco Chinesta, Emmanuelle Abisset-Chavanne, David González, 2018, Complex..

A Manifold Learning Approach to Data-Driven Computational Elasticity and Inelasticity

Francisco Chinesta, Emmanuelle Abisset-Chavanne, Jose Vicente Aguado, 2016, Archives of Computational Methods in Engineering.

kPCA-Based Parametric Solutions Within the PGD Framework

D. González, J. V. Aguado, E. Cueto, 2017 .

Proper Generalized Decompositions: An Introduction to Computer Implementation with Matlab

Icíar Alfaro, Elías Cueto, David González, 2016 .

Computational vademecums for the real-time simulation of haptic collision between nonlinear solids

Icíar Alfaro, David González, Francisco Chinesta, 2015 .

PGD-Based Computational Vademecum for Efficient Design, Optimization and Control

A. Ammar, F. Chinesta, A. Leygue, 2013, Archives of Computational Methods in Engineering.

Proper Generalized Decomposition based dynamic data driven inverse identification

E. Cueto, F. Chinesta, D. González, 2012, Math. Comput. Simul..

An augmented reality platform for interactive aerodynamic design and analysis

Icíar Alfaro, Alberto Badías, Sarah Curtit, 2019, International Journal for Numerical Methods in Engineering.

A Manifold Learning Approach to Data-Driven Computational Elasticity and Inelasticity

F. Chinesta, E. Cueto, D. González, 2016, Archives of Computational Methods in Engineering.

Computational Patient Avatars for Surgery Planning

David González, Elías Cueto, Francisco Chinesta, 2015, Annals of Biomedical Engineering.

Real-time in silico experiments on gene regulatory networks and surgery simulation on handheld devices

Adrien Leygue, Francisco Chinesta, Icíar Alfaro, 2014 .

Real‐time simulation of biological soft tissues: a PGD approach

S Niroomandi, I Alfaro, E Cueto, 2013, International journal for numerical methods in biomedical engineering.

Computational vademecums for real‐time simulation of surgical cutting in haptic environments

Francisco Chinesta, Icíar Alfaro, Elías Cueto, 2016 .

Real‐time simulation of surgery by reduced‐order modeling and X‐FEM techniques

S Niroomandi, I Alfaro, D González, 2012, International journal for numerical methods in biomedical engineering.

Deep learning of thermodynamics-aware reduced-order models from data

F. Chinesta, E. Cueto, D. González, 2020, Computer Methods in Applied Mechanics and Engineering.

Learning slosh dynamics by means of data

E. Cueto, F. Chinesta, B. Moya, 2019, Computational Mechanics.

Proper Generalized Decompositions

Icíar Alfaro, David González, Elías Cueto, 2016 .

Effect of the separated approximation of input data in the accuracy of the resulting PGD solution

A. Huerta, E. Cueto, P. Díez, 2015, Adv. Model. Simul. Eng. Sci..

Learning Corrections for Hyperelastic Models From Data

David González, Francisco Chinesta, Elías Cueto, 2019, Front. Mater..

Real‐time interaction of virtual and physical objects in mixed reality applications

Icíar Alfaro, Francisco Chinesta, Alberto Badías, 2020, International Journal for Numerical Methods in Engineering.

Towards a pancreatic surgery simulator based on model order reduction

F. Chinesta, E. Cueto, D. González, 2015, Adv. Model. Simul. Eng. Sci..

Reduced-order modeling of soft robots

Francisco Chinesta, David González, Elías Cueto, 2018, PloS one.

MORPH-DSLAM: Model Order Reduction for Physics-Based Deformable SLAM

F. Chinesta, E. Cueto, D. González, 2020, IEEE Transactions on Pattern Analysis and Machine Intelligence.

Local proper generalized decomposition

Icíar Alfaro, Elías Cueto, Francisco Chinesta, 2017 .

Vademecum‐based GFEM (V‐GFEM): optimal enrichment for transient problems

Adrien Leygue, Antonio Huerta, Francisco Chinesta, 2016 .

Towards a natural element Lagrangian strategy in fluid-structure interaction

David González, Francisco Chinesta, Manuel Doblaré, 2005 .

Physics Perception in Sloshing Scenes With Guaranteed Thermodynamic Consistency

F. Chinesta, E. Cueto, D. González, 2021, IEEE Transactions on Pattern Analysis and Machine Intelligence.

Physics-informed Reinforcement Learning for Perception and Reasoning about Fluids

F. Chinesta, E. Cueto, D. González, 2022, ArXiv.

Learning non-Markovian physics from data

Elías Cueto, Francisco Chinesta, David González, 2020, J. Comput. Phys..

Learning data-driven reduced elastic and inelastic models of spot-welded patches

Francisco Chinesta, Jean Louis Duval, Victor Champaney, 2021, Mechanics & Industry.

Real-time simulation techniques for augmented learning in science and engineering

Antonio Huerta, Icíar Alfaro, Elías Cueto, 2016, The Visual Computer.

SUPG-based stabilization of Proper Generalized Decomposition for high-dimensional Advection-Diffusion Equations

Antonio Huerta, Francisco Chinesta, David González, 2013 .

An error estimator for real-time simulators based on model order reduction

Pedro Díez, Icíar Alfaro, Elías Cueto, 2015, Adv. Model. Simul. Eng. Sci..

Hybrid Twins - a highway towards a performance-based engineering. Part I: Advanced Model Order Reduction enabling Real-Time Physics

F. Chinesta, E. Cueto, J. Duval, 2021 .

Real‐time simulation of surgery by reduced‐order modeling and X‐FEM techniques

D. González, I. Alfaro, Francisco Chinesta, 2012, International journal for numerical methods in biomedical engineering.

Multiparametric response surface construction by means of proper generalized decomposition: An extension of the PARAFAC procedure

Manuel Doblaré, David González, M. Doblaré, 2013 .

In-plane/out-of-plane separated representations of updated Lagrangian descriptions of viscoplastic flow models in plate domains

Adrien Leygue, Icíar Alfaro, Elías Cueto, 2016 .

Deep learning of thermodynamics-aware reduced-order models from data pdf

David Gonzalez, Francisco Chinesta, Quercus Hernandez, 2020, Computer Methods in Applied Mechanics and Engineering.

An error estimator for real-time simulators based on model order reduction

F. Chinesta, E. Cueto, S. Zlotnik, 2015, Advanced Modeling and Simulation in Engineering Sciences.

Computational Sensing, Understanding, and Reasoning: An Artificial Intelligence Approach to Physics-Informed World Modeling

D. González, B. Moya, Francisco Chinesta, 2023, Archives of Computational Methods in Engineering.

A thermodynamics-informed active learning approach to perception and reasoning about fluids

F. Chinesta, E. Cueto, D. González, 2022, Computational Mechanics.

Hybrid Twins. Part II. Real-time, data-driven modeling

Elías Cueto, Francisco Chinesta, Alberto Badías, 2021 .

Data-Driven GENERIC Modeling of Poroviscoelastic Materials

Icíar Alfaro, Chady Ghnatios, David González, 2019, Entropy.

Consistent data-driven computational mechanics

David González, Elías Cueto, Francisco Chinesta, 2018 .