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2020 – today
- 2024
[j47]Angel Javier Omella
, David Pardo:
r-Adaptive deep learning method for solving partial differential equations. Comput. Math. Appl. 153: 33-42 (2024)- [j46]Ignacio Brevis, Ignacio Muga, David Pardo, Oscar A. Rodríguez, Kristoffer G. van der Zee:
Learning quantities of interest from parametric PDEs: An efficient neural-weighted Minimal Residual approach. Comput. Math. Appl. 164: 139-149 (2024) - [j45]Mohammad Mahdi Abedi, David Pardo, Tariq Alkhalifah:
Ensemble Deep Learning for Enhanced Seismic Data Reconstruction. IEEE Trans. Geosci. Remote. Sens. 62: 1-11 (2024) - [i26]Jamie M. Taylor, Manuela Bastidas, Victor M. Calo, David Pardo:
Adaptive Deep Fourier Residual method via overlapping domain decomposition. CoRR abs/2401.04663 (2024) - [i25]Ibai Ramirez, Joel Pino, David Pardo, Mikel Sanz, Luis Del Rio, Alvaro Ortiz, Kateryna Morozovska, Jose Ignacio Aizpurua:
Residual-based Attention Physics-informed Neural Networks for Efficient Spatio-Temporal Lifetime Assessment of Transformers Operated in Renewable Power Plants. CoRR abs/2405.06443 (2024) - [i24]Jesus Gonzalez-Sieiro, David Pardo, Vincenzo Nava, Victor M. Calo, Markus Towara:
Reducing Spatial Discretization Error on Coarse CFD Simulations Using an OpenFOAM-Embedded Deep Learning Framework. CoRR abs/2405.07441 (2024) - [i23]Jamie M. Taylor, David Pardo, Judit Muñoz-Matute:
Regularity-Conforming Neural Networks (ReCoNNs) for solving Partial Differential Equations. CoRR abs/2405.14110 (2024) - [i22]Carlos Uriarte, Manuela Bastidas, David Pardo, Jamie M. Taylor, Sergio Rojas:
Optimizing Variational Physics-Informed Neural Networks Using Least Squares. CoRR abs/2407.20417 (2024) - 2023
- [j44]Marcin Los, Maciej Wozniak, Keshav Pingali, Luis E. García-Castillo, Julen Álvarez-Aramberri, David Pardo, Maciej Paszynski:
Fast parallel IGA-ADS solver for time-dependent Maxwell's equations. Comput. Math. Appl. 151: 36-49 (2023) - [j43]Luis F. Contreras, David Pardo, Eduardo Abreu, Judit Muñoz-Matute, Ciro Díaz, Juan Galvis:
An exponential integration generalized multiscale finite element method for parabolic problems. J. Comput. Phys. 479: 112014 (2023) - [c28]Carlos Uriarte, Jamie M. Taylor, David Pardo, Oscar A. Rodríguez, Patrick Vega:
Memory-Based Monte Carlo Integration for Solving Partial Differential Equations Using Neural Networks. ICCS (2) 2023: 509-516 - [i21]Ignacio Brevis, Ignacio Muga, David Pardo, Oscar A. Rodríguez, Kristoffer G. van der Zee:
Learning quantities of interest from parametric PDEs: An efficient neural-weighted Minimal Residual approach. CoRR abs/2304.01722 (2023) - [i20]Tomás Teijeiro, Jamie M. Taylor, Ali Hashemian, David Pardo:
Machine Learning Discovery of Optimal Quadrature Rules for Isogeometric Analysis. CoRR abs/2304.01802 (2023) - [i19]Jamie M. Taylor, Manuela Bastidas, David Pardo, Ignacio Muga:
Deep Fourier Residual method for solving time-harmonic Maxwell's equations. CoRR abs/2305.09578 (2023) - [i18]Sergio Rojas, Pawel Maczuga, Judit Muñoz-Matute, David Pardo, Maciej Paszynski:
Robust Variational Physics-Informed Neural Networks. CoRR abs/2308.16910 (2023) - 2022
- [j42]Kyubo Noh, David Pardo, Carlos Torres-Verdín:
2.5-D Deep Learning Inversion of LWD and Deep-Sensing EM Measurements Across Formations With Dipping Faults. IEEE Geosci. Remote. Sens. Lett. 19: 1-5 (2022) - [j41]Mohammad Mahdi Abedi, David Pardo:
A Multidirectional Deep Neural Network for Self-Supervised Reconstruction of Seismic Data. IEEE Trans. Geosci. Remote. Sens. 60: 1-9 (2022) - [c27]Felipe Vinicio Caro, Vincent Darrigrand, Julen Álvarez-Aramberri, Elisabete Alberdi Celaya, David Pardo:
1D Painless Multi-level Automatic Goal-Oriented h and p Adaptive Strategies Using a Pseudo-Dual Operator. ICCS (1) 2022: 347-357 - [i17]Mostafa Shahriari, David Pardo, S. Kargaran, Tomás Teijeiro:
Automated machine learning for borehole resistivity measurements. CoRR abs/2207.09849 (2022) - [i16]Angel Javier Omella, David Pardo:
r-Adaptive Deep Learning Method for Solving Partial Differential Equations. CoRR abs/2210.10900 (2022) - [i15]Jamie M. Taylor, David Pardo, Ignacio Muga:
A Deep Fourier Residual Method for solving PDEs using Neural Networks. CoRR abs/2210.14129 (2022) - [i14]Carlos Uriarte, David Pardo, Ignacio Muga, Judit Muñoz-Matute:
A Deep Double Ritz Method (D2RM) for solving Partial Differential Equations using Neural Networks. CoRR abs/2211.03627 (2022) - 2021
- [j40]Ali Hashemian, Daniel García, Jon Ander Rivera, David Pardo:
Massive database generation for 2.5D borehole electromagnetic measurements using refined isogeometric analysis. Comput. Geosci. 155: 104808 (2021) - [j39]Judit Muñoz-Matute, David Pardo, Leszek F. Demkowicz:
Equivalence between the DPG method and the exponential integrators for linear parabolic problems. J. Comput. Phys. 429: 110016 (2021) - [c26]Maciej Paszynski, Rafal Wojciech Grzeszczuk, David Pardo, Leszek F. Demkowicz:
Deep Learning Driven Self-adaptive Hp Finite Element Method. ICCS (1) 2021: 114-121 - [i13]Mostafa Shahriari, Arijit Hazra, David Pardo:
Design of borehole resistivity measurement acquisition systems using deep learning. CoRR abs/2101.05623 (2021) - [i12]Jon Ander Rivera, Jamie M. Taylor, Angel Javier Omella, David Pardo:
On quadrature rules for solving Partial Differential Equations using Neural Networks. CoRR abs/2111.00217 (2021) - [i11]Kyubo Noh, David Pardo, Carlos Torres-Verdín:
Deep-Learning Inversion Method for the Interpretation of Noisy Logging-While-Drilling Resistivity Measurements. CoRR abs/2111.07490 (2021) - [i10]Ali Hashemian, Daniel García, David Pardo, Victor M. Calo:
Performance of Refined Isogeometric Analysis in Solving Quadratic Eigenvalue Problems. CoRR abs/2112.14064 (2021) - 2020
- [c25]Jon Ander Rivera, David Pardo, Elisabete Alberdi:
Design of Loss Functions for Solving Inverse Problems Using Deep Learning. ICCS (3) 2020: 158-171 - [i9]Mostafa Shahriari, David Pardo, J. A. Rivera, Carlos Torres-Verdín, Artzai Picón, Javier Del Ser, S. Ossandón, Victor M. Calo:
Error Control and Loss Functions for the Deep Learning Inversion of Borehole Resistivity Measurements. CoRR abs/2005.08868 (2020) - [i8]Sergey Alyaev, Mostafa Shahriari, David Pardo, Angel Javier Omella, David Larsen, Nazanin Jahani, Erich Suter:
Modeling extra-deep EM logs using a deep neural network. CoRR abs/2005.08919 (2020) - [i7]Sergio Rojas, David Pardo, Pouria Behnoudfar, Victor M. Calo:
Residual minimization for goal-oriented adaptivity. CoRR abs/2007.08824 (2020) - [i6]Ali Hashemian, Daniel García, Jon Ander Rivera, David Pardo:
Database Generation for Deep Learning Inversion of 2.5D Borehole Electromagnetic Measurements using Refined Isogeometric Analysis. CoRR abs/2009.08132 (2020) - [i5]Ali Hashemian, David Pardo, Victor M. Calo:
Refined isogeometric analysis for generalized Hermitian eigenproblems. CoRR abs/2009.08167 (2020)
2010 – 2019
- 2019
- [j38]Ignacio Brevis, Ángel Rodríguez-Rozas, Jaime H. Ortega, David Pardo:
Source time reversal (STR) method for linear elasticity. Comput. Math. Appl. 77(5): 1358-1375 (2019) - [j37]Leszek Siwik, Maciej Wozniak, Victor Trujillo, David Pardo, Victor Manuel Calo, Maciej Paszynski:
Parallel Refined Isogeometric Analysis in 3D. IEEE Trans. Parallel Distributed Syst. 30(5): 1134-1142 (2019) - 2018
- [j36]A. Erdozain, Victor Péron, David Pardo:
Asymptotic models for the electric potential across a highly conductive casing. Comput. Math. Appl. 76(8): 1975-2000 (2018) - [j35]Théophile Chaumont-Frelet, Serge Nicaise, David Pardo:
Finite Element Approximation of Electromagnetic Fields Using Nonfitting Meshes for Geophysics. SIAM J. Numer. Anal. 56(4): 2288-2321 (2018) - [i4]Mostafa Shahriari, David Pardo, Artzai Picón, Adrian Galdran, Javier Del Ser, Carlos Torres-Verdín:
A Deep Learning Approach to the Inversion of Borehole Resistivity Measurements. CoRR abs/1810.04522 (2018) - 2017
- [j34]Ewa Gajda-Zagórska, Robert Schaefer, Maciej Smolka, David Pardo, Julen Álvarez-Aramberri:
A multi-objective memetic inverse solver reinforced by local optimization methods. J. Comput. Sci. 18: 85-94 (2017) - [j33]Julen Álvarez-Aramberri, David Pardo:
Dimensionally adaptive hp-finite element simulation and inversion of 2D magnetotelluric measurements. J. Comput. Sci. 18: 95-105 (2017) - [j32]Adrian Galdran, Javier Vazquez-Corral, David Pardo, Marcelo Bertalmío:
Fusion-Based Variational Image Dehazing. IEEE Signal Process. Lett. 24(2): 151-155 (2017) - [c24]Aleksander Byrski, Maciej Paszynski, Robert Schaefer, Victor M. Calo, David Pardo:
ICCS 2017 Workshop on Agent-Based Simulations, Adaptive Algorithms and Solvers. ICCS 2017: 796-797 - [c23]Daniel García, Michael Barton, David Pardo:
Optimally refined isogeometric analysis. ICCS 2017: 808-817 - [c22]Vincent Darrigrand, Ángel Rodríguez-Rozas, David Pardo, Ignacio Muga:
Goal-Oriented p-Adaptivity using Unconventional Error Representations for a 1D Steady State Convection-Diffusion Problem. ICCS 2017: 848-856 - 2016
- [c21]Javier Vazquez-Corral, Syed Waqas Zamir, Adrian Galdran, David Pardo, Marcelo Bertalmío:
Image processing applications through a variational perceptually-based color correction related to Retinex. Retinex at 50 2016: 1-6 - [c20]Ángel Rodríguez-Rozas, David Pardo:
A Priori Fourier Analysis for 2.5D Finite Elements Simulations of Logging-while-drilling (LWD) Resistivity Measurements. ICCS 2016: 782-791 - 2015
- [j31]Maciej Smolka, Robert Schaefer, Maciej Paszynski, David Pardo, Julen Álvarez-Aramberri:
An Agent-Oriented Hierarchic Strategy for Solving Inverse Problems. Int. J. Appl. Math. Comput. Sci. 25(3): 483-498 (2015) - [j30]Maciej Smolka, Ewa Gajda-Zagórska, Robert Schaefer, Maciej Paszynski, David Pardo:
A hybrid method for inversion of 3D AC resistivity logging measurements. Appl. Soft Comput. 36: 442-456 (2015) - [j29]Arkadiusz Szymczak, Maciej Paszynski, David Pardo, Anna Paszynska:
Petri Nets Modeling of Dead-End Refinement Problems in a 3D Anisotropic hp-Adaptive Finite Element Method. Comput. Informatics 34(2): 425-457 (2015) - [j28]Vincent Darrigrand, David Pardo, Ignacio Muga:
Goal-oriented adaptivity using unconventional error representations for the 1D Helmholtz equation. Comput. Math. Appl. 69(9): 964-979 (2015) - [j27]Maciej Paszynski, David Pardo, Victor M. Calo:
Direct solvers performance on h-adapted grids. Comput. Math. Appl. 70(3): 282-295 (2015) - [j26]Ignacio Muga, David Pardo, Pawel Jerzy Matuszyk, Carlos Torres-Verdín:
Semi-analytical response of acoustic logging measurements in frequency domain. Comput. Math. Appl. 70(4): 314-329 (2015) - [j25]David Pardo, Julen Álvarez-Aramberri, Maciej Paszynski, Lisandro Dalcín, Victor M. Calo:
Impact of element-level static condensation on iterative solver performance. Comput. Math. Appl. 70(10): 2331-2341 (2015) - [j24]Ignacio Gómez-Revuelto, Luis E. García-Castillo, David Pardo:
High-accuracy adaptive modeling of the energy distribution of a meniscus-shaped cell culture in a Petri dish. J. Comput. Sci. 9: 143-149 (2015) - [j23]Julen Álvarez-Aramberri, David Pardo, Helene Barucq:
A secondary field based hp-Finite Element Method for the simulation of magnetotelluric measurements. J. Comput. Sci. 11: 137-144 (2015) - [j22]Adrian Galdran, David Pardo, Artzai Picón, Aitor Alvarez-Gila:
Automatic Red-Channel underwater image restoration. J. Vis. Commun. Image Represent. 26: 132-145 (2015) - [j21]Ewa Gajda-Zagórska, Robert Schaefer, Maciej Smolka, Maciej Paszynski, David Pardo:
A hybrid method for inversion of 3D DC resistivity logging measurements. Nat. Comput. 14(3): 355-374 (2015) - [j20]Adrian Galdran, Javier Vazquez-Corral, David Pardo, Marcelo Bertalmío:
Enhanced Variational Image Dehazing. SIAM J. Imaging Sci. 8(3): 1519-1546 (2015) - [c19]Adrian Galdran, Artzai Picón, Estíbaliz Garrote, David Pardo:
Pectoral Muscle Segmentation in Mammograms Based on Cartoon-Texture Decomposition. IbPRIA 2015: 587-594 - [c18]Julen Álvarez-Aramberri, Shaaban Ali Bakr, David Pardo, Helene Barucq:
Quantities of Interest for Surface based Resistivity Geophysical Measurements. ICCS 2015: 964-973 - [c17]Ewa Gajda-Zagórska, Maciej Smolka, Robert Schaefer, David Pardo, Julen Álvarez-Aramberri:
Multi-objective Hierarchic Memetic Solver for Inverse Parametric Problems. ICCS 2015: 974-983 - 2014
- [j19]Maciej Wozniak, Krzysztof Kuznik, Maciej Paszynski, Victor M. Calo, David Pardo:
Computational cost estimates for parallel shared memory isogeometric multi-frontal solvers. Comput. Math. Appl. 67(10): 1864-1883 (2014) - [j18]I. Gómez-Revuelto, L. E. García-Castillo, S. Llorente-Romano, David Pardo:
3D hp-adaptive finite element simulations of bend, step, and magic-T electromagnetic waveguide structures. J. Comput. Sci. 5(2): 65-75 (2014) - [c16]Adrian Galdran, Javier Vazquez-Corral, David Pardo, Marcelo Bertalmío:
A Variational Framework for Single Image Dehazing. ECCV Workshops (3) 2014: 259-270 - [c15]Julen Álvarez-Aramberri, David Pardo, Helene Barucq:
Automatically Adapted Perfectly Matched Layers for Problems with High Contrast Materials Properties. ICCS 2014: 970-979 - 2013
- [j17]Ewa Gajda-Zagórska, Maciej Paszynski, Robert Schaefer, David Pardo:
hp-HGS strategy for inverse AC/DC resistivity logging measurement simulations. Comput. Sci. 14(4): 629-644 (2013) - [j16]Maciej Paszynski, David Pardo, Victor M. Calo:
A direct solver with reutilization of LU factorizations for hh-adaptive finite element grids with point singularities. Comput. Math. Appl. 65(8): 1140-1151 (2013) - [j15]Shaaban Ali Bakr, David Pardo, Trond Mannseth:
Domain decomposition Fourier finite element method for the simulation of 3D marine CSEM measurements. J. Comput. Phys. 255: 456-470 (2013) - [j14]Maciej Paszynski, Krzysztof Cetnarowicz, Robert Schaefer, David Pardo, Victor M. Calo:
Preface. J. Comput. Sci. 4(3): 125-126 (2013) - [j13]Arkadiusz Szymczak, Anna Paszynska, Maciej Paszynski, David Pardo:
Preventing deadlock during anisotropic 2D mesh adaptation in hp-adaptive FEM. J. Comput. Sci. 4(3): 170-179 (2013) - [j12]Nathan O. Collier, Lisandro Dalcín, David Pardo, Victor M. Calo:
The Cost of Continuity: Performance of Iterative Solvers on Isogeometric Finite Elements. SIAM J. Sci. Comput. 35(2) (2013) - [c14]I. Gómez-Revuelto, L. E. García-Castillo, David Pardo:
High-Accuracy Adaptive Simulations of a Petri Dish Exposed to Electromagnetic Radiation. ICCS 2013: 1555-1563 - [c13]Julen Álvarez-Aramberri, David Pardo, Helene Barucq:
Inversion of Magnetotelluric Measurements Using Multigoal Oriented hp-Adaptivity. ICCS 2013: 1564-1573 - 2012
- [j11]Gorka Garate, Ernesto G. Vadillo, Javier Santamaria, David Pardo:
Solution of the 3D-Helmholtz equation in exterior domains using spherical harmonic decomposition. Comput. Math. Appl. 64(8): 2520-2543 (2012) - [c12]Ewa Gajda-Zagórska, Maciej Paszynski, Robert Schaefer, David Pardo, Victor M. Calo:
hp-HGS strategy for inverse 3D DC resistivity logging measurement simulations. ICCS 2012: 927-936 - [c11]Anna Paszynska, Maciej Paszynski, Arkadiusz Szymczak, David Pardo:
Petri Nets for Detecting a 3D Deadlock Problem in Hp-adaptive Finite Element Simulations. ICCS 2012: 1434-1443 - [c10]I. Gómez-Revuelto, L. E. García-Castillo, S. Llorente-Romano, David Pardo:
3D hp-Adaptive Finite Element Simulations of a Magic-T Electromagnetic Waveguide Structure. ICCS 2012: 1444-1453 - [c9]Julen Álvarez-Aramberri, David Pardo, Maciej Paszynski, Nathan O. Collier, Lisandro Dalcín, Victor M. Calo:
On Round-off Error for Adaptive Finite Element Methods. ICCS 2012: 1474-1483 - [i3]Nathan O. Collier, David Pardo, Maciej Paszynski, Victor M. Calo:
Computational complexity and memory usage for multi-frontal direct solvers in structured mesh finite elements. CoRR abs/1204.1718 (2012) - [i2]Nathan O. Collier, Lisandro Dalcín, David Pardo, Victor M. Calo:
The cost of continuity: performance of iterative solvers on isogeometric finite elements. CoRR abs/1206.2948 (2012) - [i1]Maciej Paszynski, Victor M. Calo, David Pardo:
A direct solver with reutilization of previously-computed LU factorizations for h-adaptive finite element grids with point singularities. CoRR abs/1212.1992 (2012) - 2011
- [j10]Maciej Paszynski, Tomasz Jurczyk, David Pardo:
Multi-frontal Solver for Simulations of Linear Elasticity coupled with Acoustics. Comput. Sci. 12: 85-102 (2011) - [j9]J. Zitelli, Ignacio Muga, Leszek F. Demkowicz, Jayadeep Gopalakrishnan, David Pardo, Victor M. Calo:
A class of discontinuous Petrov-Galerkin methods. Part IV: The optimal test norm and time-harmonic wave propagation in 1D. J. Comput. Phys. 230(7): 2406-2432 (2011) - [j8]David Pardo, Pawel Jerzy Matuszyk, Ignacio Muga, Carlos Torres-Verdín, Angel Mora, Victor M. Calo:
Simulation of wireline sonic logging measurements acquired with Borehole-Eccentered tools using a high-order adaptive finite-element method. J. Comput. Phys. 230(16): 6320-6333 (2011) - [c8]Victor M. Calo, David Pardo, Maciej Paszynski:
Goal-Oriented Self-Adaptive hp Finite Element Simulation of 3D DC Borehole Resistivity Simulations. ICCS 2011: 1485-1495 - [c7]Maciej Paszynski, David Pardo, Anna Paszynska, Leszek F. Demkowicz:
Out-of-core multi-frontal solver for multi-physics hp adaptive problems. ICCS 2011: 1788-1797 - [c6]Arkadiusz Szymczak, Anna Paszynska, Maciej Paszynski, David Pardo:
Anisotropic 2D mesh adaptation in hp-adaptive FEM. ICCS 2011: 1818-1827 - [c5]Victor M. Calo, Nathan O. Collier, David Pardo, Maciej Paszynski:
Computational complexity and memory usage for multi-frontal direct solvers used in p finite element analysis. ICCS 2011: 1854-1861 - 2010
- [j7]Arkadiusz Szymczak, Maciej Paszynski, David Pardo:
Graph Grammar Based Petri Net Controlled Direct Solver Algorithm. Comput. Sci. 11: 65-80 (2010) - [j6]Maciej Paszynski, David Pardo, Anna Paszynska:
Parallel multi-frontal solver for p adaptive finite element modeling of multi-physics computational problems. J. Comput. Sci. 1(1): 48-54 (2010) - [j5]Maciej Paszynski, David Pardo, Carlos Torres-Verdín, Leszek F. Demkowicz, Victor M. Calo:
A parallel direct solver for the self-adaptive hp Finite Element Method. J. Parallel Distributed Comput. 70(3): 270-281 (2010) - [j4]Qing Chen, David Pardo, Hongbin Li, Furong Wang, Qi-zheng Ye:
Arithmetic Method of Double-Injection-Electrode Model for Resistivity Measurement Through Metal Casing. IEEE Trans. Geosci. Remote. Sens. 48(1-1): 36-41 (2010) - [c4]Krzysztof Cetnarowicz, Maciej Paszynski, David Pardo, Tibor Bosse, Han La Poutré:
Agent-based computing, adaptive algorithms and bio computing. ICCS 2010: 1951-1952 - [c3]David Pardo:
Multigoal-oriented adaptivity for hp-finite element methods. ICCS 2010: 1953-1961 - [c2]Maciej Paszynski, David Pardo, Anna Paszynska:
Parallel multi-frontal solver for multi-physics p adaptive problems. ICCS 2010: 1983-1992
2000 – 2009
- 2008
- [j3]David Pardo, Leszek F. Demkowicz, Carlos Torres-Verdín, C. Michler:
PML Enhanced with a Self-Adaptive Goal-Oriented hp-Finite Element Method: Simulation of Through-Casing Borehole Resistivity Measurements. SIAM J. Sci. Comput. 30(6): 2948-2964 (2008) - 2006
- [j2]David Pardo, Leszek F. Demkowicz, Carlos Torres-Verdín, Maciej Paszynski:
Two-Dimensional High-Accuracy Simulation of Resistivity Logging-While-Drilling (LWD) Measurements Using a Self-Adaptive Goal-Oriented hp Finite Element Method. SIAM J. Appl. Math. 66(6): 2085-2106 (2006) - [j1]David Pardo, Carlos Torres-Verdín, Leszek F. Demkowicz:
Simulation of multifrequency borehole resistivity measurements through metal casing using a goal-oriented hp finite-element method. IEEE Trans. Geosci. Remote. Sens. 44(8): 2125-2134 (2006) - [c1]Maciej Paszynski, David Pardo, Leszek F. Demkowicz, Carlos Torres-Verdín:
Parallel hp-Finite Element Simulations of 3D Resistivity Logging Instruments. CE 2006: 635-642
Coauthor Index
Victor M. Calo
aka: Victor Manuel Calo
aka: Victor Manuel Calo
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