DAVID
PARDO ZUBIAUR
INVESTIGADOR/A DISTINGUIDO/A
JUDIT
MUÑOZ MATUTE
INVESTIGADOR/A DOCTOR/A
2025
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Regularity-conforming neural networks (ReCoNNs) for solving partial differential equations
Journal of Computational Physics, Vol. 532
2024
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Robust Variational Physics-Informed Neural Networks
Computer Methods in Applied Mechanics and Engineering, Vol. 425
2023
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A Deep Double Ritz Method (D2RM) for solving Partial Differential Equations using Neural Networks
Computer Methods in Applied Mechanics and Engineering, Vol. 405
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An exponential integration generalized multiscale finite element method for parabolic problems
Journal of Computational Physics, Vol. 479
2022
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Exploiting the Kronecker product structure of φ−functions in exponential integrators
International Journal for Numerical Methods in Engineering, Vol. 123, Núm. 9, pp. 2142-2161
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Solving Partial Differential Equations using Adversarial Neural Networks
Congress on Numerical Methods in Engineering CMN 2022 (2022. Las Palmas de Gran Canaria)
2021
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A DPG-based time-marching scheme for linear hyperbolic problems
Computer Methods in Applied Mechanics and Engineering, Vol. 373
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Equivalence between the DPG method and the exponential integrators for linear parabolic problems
Journal of Computational Physics, Vol. 429
2019
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Explicit-in-time goal-oriented adaptivity
Computer Methods in Applied Mechanics and Engineering, Vol. 347, pp. 176-200
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Forward-in-time goal-oriented adaptivity
International Journal for Numerical Methods in Engineering, Vol. 119, Núm. 6, pp. 490-505
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Variational formulations for explicit Runge-Kutta Methods
Finite Elements in Analysis and Design, Vol. 165, pp. 77-93
2017
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Time-domain goal-oriented adaptivity using pseudo-dual error representations
Computer Methods in Applied Mechanics and Engineering, Vol. 325, pp. 395-415