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ORCIDJuan A. Acebrón
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2020 – today
- 2024
[j19]Nicolas L. Guidotti
, Juan A. Acebrón, José Monteiro:
A stochastic method for solving time-fractional differential equations. Comput. Math. Appl. 159: 240-253 (2024)- [j18]Nicolas L. Guidotti, Juan A. Acebrón, José Monteiro:
A Fast Monte Carlo Algorithm for Evaluating Matrix Functions with Application in Complex Networks. J. Sci. Comput. 99(2): 41 (2024) - [i7]Inês A. Ferreira, Juan A. Acebrón, José Monteiro:
Survey of a Class of Iterative Row-Action Methods: The Kaczmarz Method. CoRR abs/2401.02842 (2024) - [i6]Inês A. Ferreira, Juan A. Acebrón, José Monteiro:
Parallelization Strategies for the Randomized Kaczmarz Algorithm on Large-Scale Dense Systems. CoRR abs/2401.17474 (2024) - [i5]Juan A. Acebrón, Ángel Rodríguez-Rozas:
A new parallel solver suited for arbitrary semilinear parabolic partial differential equations based on generalized random trees. CoRR abs/2402.06491 (2024) - [i4]Andrés Centeno, Juan A. Acebrón, José Monteiro:
Sensitivity analysis of fractional linear systems based on random walks with negligible memory usage. CoRR abs/2408.04351 (2024) - 2023
- [j17]Francisco Bernal, Jorge Morón-Vidal, Juan A. Acebrón:
A hybrid probabilistic domain decomposition algorithm suited for very large-scale elliptic PDEs. Comput. Math. Appl. 146: 294-308 (2023) - [i3]Francisco Bernal, Jorge Morón-Vidal, Juan A. Acebrón:
A hybrid probabilistic domain decomposition algorithm suited for very large-scale elliptic PDEs. CoRR abs/2301.05780 (2023) - [i2]Nicolas L. Guidotti, Juan A. Acebrón, José Monteiro:
A Stochastic Method for Solving Time-Fractional Differential Equations. CoRR abs/2303.15458 (2023) - [i1]Nicolas L. Guidotti, Juan A. Acebrón, José Monteiro:
A Fast Monte Carlo algorithm for evaluating matrix functions with application in complex networks. CoRR abs/2308.01037 (2023) - 2022
- [j16]Filipe Magalhães, José Monteiro, Juan A. Acebrón, José R. Herrero:
A distributed Monte Carlo based linear algebra solver applied to the analysis of large complex networks. Future Gener. Comput. Syst. 127: 320-330 (2022) - 2020
- [j15]Juan A. Acebrón, José R. Herrero, José Monteiro:
A highly parallel algorithm for computing the action of a matrix exponential on a vector based on a multilevel Monte Carlo method. Comput. Math. Appl. 79(12): 3495-3515 (2020) - [j14]Juan A. Acebrón:
A Probabilistic Linear Solver Based on a Multilevel Monte Carlo Method. J. Sci. Comput. 82(3): 65 (2020)
2010 – 2019
- 2019
- [j13]Juan A. Acebrón:
A Monte Carlo method for computing the action of a matrix exponential on a vector. Appl. Math. Comput. 362 (2019) - 2016
- [j12]Francisco Bernal, Juan A. Acebrón:
A multigrid-like algorithm for probabilistic domain decomposition. Comput. Math. Appl. 72(7): 1790-1810 (2016) - [j11]Juan A. Acebrón, Marco A. Ribeiro:
A Monte Carlo method for solving the one-dimensional telegraph equations with boundary conditions. J. Comput. Phys. 305: 29-43 (2016) - [j10]Sara Mancini, Francisco Bernal, Juan A. Acebrón:
An Efficient Algorithm for Accelerating Monte Carlo Approximations of the Solution to Boundary Value Problems. J. Sci. Comput. 66(2): 577-597 (2016) - 2014
- [j9]Francisco Bernal, Juan A. Acebrón, Immanuel Anjam:
A Stochastic Algorithm Based on Fast Marching for Automatic Capacitance Extraction in Non-Manhattan Geometries. SIAM J. Imaging Sci. 7(4): 2657-2674 (2014) - 2013
- [j8]Juan A. Acebrón, Ángel Rodríguez-Rozas:
Highly efficient numerical algorithm based on random trees for accelerating parallel Vlasov-Poisson simulations. J. Comput. Phys. 250: 224-245 (2013) - 2011
- [j7]Juan A. Acebrón, Ángel Rodríguez-Rozas:
A new parallel solver suited for arbitrary semilinear parabolic partial differential equations based on generalized random trees. J. Comput. Phys. 230(21): 7891-7909 (2011) - 2010
- [j6]Juan A. Acebrón, Ángel Rodríguez-Rozas, Renato Spigler:
A fully scalable algorithm suited for petascale computing and beyond. Comput. Sci. Res. Dev. 25(1-2): 115-121 (2010) - [j5]Juan A. Acebrón, Ángel Rodríguez-Rozas, Renato Spigler:
Efficient Parallel Solution of Nonlinear Parabolic Partial Differential Equations by a Probabilistic Domain Decomposition. J. Sci. Comput. 43(2): 135-157 (2010)
2000 – 2009
- 2009
- [j4]Juan A. Acebrón, Ángel Rodríguez-Rozas, Renato Spigler:
Domain decomposition solution of nonlinear two-dimensional parabolic problems by random trees. J. Comput. Phys. 228(15): 5574-5591 (2009) - [c6]Juan A. Acebrón, Ángel Rodríguez-Rozas, Renato Spigler:
On the Performance of a New Parallel Algorithm for Large-Scale Simulations of Nonlinear Partial Differential Equations. PPAM (1) 2009: 41-50 - [c5]R. Rico López, V. Escuder Cabañas, Raúl Durán Díaz, L. E. García-Castillo, I. Gómez-Revuelto, Juan A. Acebrón:
Parallelising a simulator for the analysis of electromagnetic radiation using MUMPS library. VALUETOOLS 2009: 29 - 2007
- [j3]Juan A. Acebrón, Renato Spigler:
Supercomputing applications to the numerical modeling of industrial and applied mathematics problems. J. Supercomput. 40(1): 67-80 (2007) - [c4]Juan A. Acebrón, Renato Spigler:
A Fully Scalable Parallel Algorithm for Solving Elliptic Partial Differential Equations. Euro-Par 2007: 727-736 - [c3]Juan A. Acebrón, Renato Spigler:
Scalability and Performance Analysis of a Probabilistic Domain Decomposition Method. PPAM 2007: 1257-1264 - 2006
- [c2]Juan A. Acebrón, Raúl Durán, Rafael Rico, Renato Spigler:
A New Domain Decomposition Approach Suited for Grid Computing. PARA 2006: 744-753 - 2005
- [j2]Juan A. Acebrón, Renato Spigler:
Second Harmonics Effects in Random Duffing Oscillators. SIAM J. Appl. Math. 66(1): 266-285 (2005) - [j1]Juan A. Acebrón, Maria Pia Busico, Piero Lanucara, Renato Spigler:
Domain Decomposition Solution of Elliptic Boundary-Value Problems via Monte Carlo and Quasi-Monte Carlo Methods. SIAM J. Sci. Comput. 27(2): 440-457 (2005) - 2002
- [c1]Juan A. Acebrón, Adi R. Bulsara, W.-J. Rappel:
Noise-mediated cooperative behavior in a system of coupled DC SQUIDs. ISCAS (4) 2002: 293-296
Coauthor Index
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