D. González, F. Chinesta, E. Cueto. Learning Corrections for Hyperelastic Models From Data. Front. Mater. 6 (2019) DOI 10.3389/fmats.2019.00014
B. Hashemian, D. Millán, M. Arroyo. Modeling and enhanced sampling of molecular systems with smooth and nonlinear data-driven collective variables. The Journal of Chemical Physics 139(21) DOI 10.1063/1.4830403
D. González, E. Cueto, F. Chinesta. Real-time direct integration of reduced solid dynamics equations. Int. J. Numer. Meth. Engng 99(9) (2014) DOI 10.1002/nme.4691
F. Naets, D. De Gregoriis, W. Desmet. Multi‐expansion modal reduction: A pragmatic semi–a priori model order reduction approach for nonlinear structural dynamics. Int J Numer Methods Eng 118(13) (2019) DOI 10.1002/nme.6034
D. González, F. Chinesta, E. Cueto. Thermodynamically consistent data-driven computational mechanics. Continuum Mech. Thermodyn. 31(1) (2018) DOI 10.1007/s00161-018-0677-z
J. Gaudêncio, F. de Almeida, R. Sabioni, J. Turrioni, A. de Paiva, P. da Silva Campos. Fuzzy multivariate mean square error in equispaced pareto frontiers considering manufacturing process optimization problems. Engineering with Computers 35(4) (2018) DOI 10.1007/s00366-018-0660-0
S. Jain, P. Tiso. Hyper-Reduction Over Nonlinear Manifolds for Large Nonlinear Mechanical Systems. 14(8) (2019) DOI 10.1115/1.4043450
F. Greco, L. Filice, C. Peco, M. Arroyo. A stabilized formulation with maximum entropy meshfree approximants for viscoplastic flow simulation in metal forming. Int J Mater Form 8(3) (2014) DOI 10.1007/s12289-014-1167-x
D. González, J. Aguado, E. Cueto, E. Abisset-Chavanne, F. Chinesta. kPCA-Based Parametric Solutions Within the PGD Framework. Arch Computat Methods Eng 25(1) (2016) DOI 10.1007/s11831-016-9173-4
Q. He, J. Chen, C. Marodon. A decomposed subspace reduction for fracture mechanics based on the meshfree integrated singular basis function method. Comput Mech 63(3) (2018) DOI 10.1007/s00466-018-1611-8
R. Ibañez, E. Abisset-Chavanne, E. Cueto, A. Ammar, J. Duval, F. Chinesta. Some applications of compressed sensing in computational mechanics: model order reduction, manifold learning, data-driven applications and nonlinear dimensionality reduction. Comput Mech 64(5) (2019) DOI 10.1007/s00466-019-01703-5
B. Moya, D. Gonzalez, I. Alfaro, F. Chinesta, E. Cueto. Learning slosh dynamics by means of data. Comput Mech 64(2) (2019) DOI 10.1007/s00466-019-01705-3