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Pietro Marco Congedo
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2020 – today
- 2024
 [j17]Paul Novello [j17]Paul Novello , Gaël Poëtte, David Lugato, Simon Peluchon, Pietro Marco Congedo: , Gaël Poëtte, David Lugato, Simon Peluchon, Pietro Marco Congedo:
 Accelerating hypersonic reentry simulations using deep learning-based hybridization (with guarantees). J. Comput. Phys. 498: 112700 (2024)
- 2023
 [j16]Paul Novello [j16]Paul Novello , Gaël Poëtte, David Lugato, Pietro Marco Congedo: , Gaël Poëtte, David Lugato, Pietro Marco Congedo:
 Goal-Oriented Sensitivity Analysis of Hyperparameters in Deep Learning. J. Sci. Comput. 94(3): 45 (2023)
- 2022
 [j15]Paola Bacigaluppi [j15]Paola Bacigaluppi , Julien Carlier, Marica Pelanti, Pietro Marco Congedo, Rémi Abgrall , Julien Carlier, Marica Pelanti, Pietro Marco Congedo, Rémi Abgrall : :
 Assessment of a Non-Conservative Four-Equation Multiphase System with Phase Transition. J. Sci. Comput. 90(1): 28 (2022)
 [j14]Mickael Rivier [j14]Mickael Rivier , Pietro Marco Congedo: , Pietro Marco Congedo:
 Surrogate-Assisted Bounding-Box approach applied to constrained multi-objective optimisation under uncertainty. Reliab. Eng. Syst. Saf. 217: 108039 (2022)
 [i5]Paul Novello, Gaël Poëtte, David Lugato, Pietro Marco Congedo: [i5]Paul Novello, Gaël Poëtte, David Lugato, Pietro Marco Congedo:
 Goal-Oriented Sensitivity Analysis of Hyperparameters in Deep Learning. CoRR abs/2207.06216 (2022)
 [i4]Paul Novello, Gaël Poëtte, David Lugato, Simon Peluchon, Pietro Marco Congedo: [i4]Paul Novello, Gaël Poëtte, David Lugato, Simon Peluchon, Pietro Marco Congedo:
 Accelerating hypersonic reentry simulations using deep learning-based hybridization (with guarantees). CoRR abs/2209.13434 (2022)
- 2021
 [i3]Paul Novello, Gaël Poëtte, David Lugato, Pietro Marco Congedo: [i3]Paul Novello, Gaël Poëtte, David Lugato, Pietro Marco Congedo:
 Variance Based Samples Weighting for Supervised Deep Learning. CoRR abs/2101.07561 (2021)
 [i2]Paola Bacigaluppi [i2]Paola Bacigaluppi , Julien Carlier, Marica Pelanti, Pietro Marco Congedo, Rémi Abgrall: , Julien Carlier, Marica Pelanti, Pietro Marco Congedo, Rémi Abgrall:
 Assessment of a non-conservative four-equation multiphase system with phase transition. CoRR abs/2105.12874 (2021)
- 2020
 [j13]Andrea F. Cortesi, Paul G. Constantine [j13]Andrea F. Cortesi, Paul G. Constantine , Thierry E. Magin , Thierry E. Magin , Pietro Marco Congedo: , Pietro Marco Congedo:
 Forward and backward uncertainty quantification with active subspaces: Application to hypersonic flows around a cylinder. J. Comput. Phys. 407: 109079 (2020)
 [j12]Nassim Razaaly, Pietro Marco Congedo: [j12]Nassim Razaaly, Pietro Marco Congedo:
 Extension of AK-MCS for the efficient computation of very small failure probabilities. Reliab. Eng. Syst. Saf. 203: 107084 (2020)
 [i1]Anabel del Val, Olivier P. Le Maître, Olivier Chazot, Thierry E. Magin, Pietro Marco Congedo: [i1]Anabel del Val, Olivier P. Le Maître, Olivier Chazot, Thierry E. Magin, Pietro Marco Congedo:
 A surrogate-based optimal likelihood function for the Bayesian calibration of catalytic recombination in atmospheric entry protection materials. CoRR abs/2010.04649 (2020)
2010 – 2019
- 2019
 [j11]Andrea F. Cortesi, Ghina Jannoun, Pietro Marco Congedo: [j11]Andrea F. Cortesi, Ghina Jannoun, Pietro Marco Congedo:
 Kriging-sparse Polynomial Dimensional Decomposition surrogate model with adaptive refinement. J. Comput. Phys. 380: 212-242 (2019)
 [j10]Mickael Rivier, Pietro Marco Congedo: [j10]Mickael Rivier, Pietro Marco Congedo:
 Surrogate-assisted Bounding-Box approach for optimization problems with tunable objectives fidelity. J. Glob. Optim. 75(4): 1079-1109 (2019)
- 2018
 [j9]Nassim Razaaly, Pietro Marco Congedo: [j9]Nassim Razaaly, Pietro Marco Congedo:
 Novel algorithm using Active Metamodel Learning and Importance Sampling: Application to multiple failure regions of low probability. J. Comput. Phys. 368: 92-114 (2018)
- 2017
 [j8]Rémi Abgrall [j8]Rémi Abgrall , Pietro Marco Congedo, Gianluca Geraci: , Pietro Marco Congedo, Gianluca Geraci:
 Towards a unified multiresolution scheme for treating discontinuities in differential equations with uncertainties. Math. Comput. Simul. 139: 1-22 (2017)
- 2016
 [j7]Francesca Fusi, Pietro Marco Congedo: [j7]Francesca Fusi, Pietro Marco Congedo:
 An adaptive strategy on the error of the objective functions for uncertainty-based derivative-free optimization. J. Comput. Phys. 309: 241-266 (2016)
 [j6]Kunkun Tang [j6]Kunkun Tang , Pietro Marco Congedo, Rémi Abgrall , Pietro Marco Congedo, Rémi Abgrall : :
 Adaptive surrogate modeling by ANOVA and sparse polynomial dimensional decomposition for global sensitivity analysis in fluid simulation. J. Comput. Phys. 314: 557-589 (2016)
 [j5]Gianluca Geraci, Pietro Marco Congedo, Rémi Abgrall [j5]Gianluca Geraci, Pietro Marco Congedo, Rémi Abgrall , Gianluca Iaccarino: , Gianluca Iaccarino:
 A Novel Weakly-Intrusive Non-linear Multiresolution Framework for Uncertainty Quantification in Hyperbolic Partial Differential Equations. J. Sci. Comput. 66(1): 358-405 (2016)
- 2015
 [j4]Rémi Abgrall [j4]Rémi Abgrall , Pietro Marco Congedo, Gianluca Geraci, Maria Giovanna Rodio: , Pietro Marco Congedo, Gianluca Geraci, Maria Giovanna Rodio:
 Stochastic Discrete Equation Method (sDEM) for two-phase flows. J. Comput. Phys. 299: 281-306 (2015)
- 2014
 [j3]Rémi Abgrall [j3]Rémi Abgrall , Pietro Marco Congedo, Gianluca Geraci: , Pietro Marco Congedo, Gianluca Geraci:
 A one-time truncate and encode multiresolution stochastic framework. J. Comput. Phys. 257: 19-56 (2014)
- 2013
 [j2]Pietro Marco Congedo, Jeroen A. S. Witteveen [j2]Pietro Marco Congedo, Jeroen A. S. Witteveen , Gianluca Iaccarino: , Gianluca Iaccarino:
 A simplex-based numerical framework for simple and efficient robust design optimization. Comput. Optim. Appl. 56(1): 231-251 (2013)
 [j1]Rémi Abgrall, Pietro Marco Congedo: [j1]Rémi Abgrall, Pietro Marco Congedo:
 A semi-intrusive deterministic approach to uncertainty quantification in non-linear fluid flow problems. J. Comput. Phys. 235: 828-845 (2013)
2000 – 2009
- 2007
 [b1]Pietro Marco Congedo: [b1]Pietro Marco Congedo:
 Analysis and Optimization of Dense gas flows: Application to organic Rankine cycles turbines. University of Salento, Lecce, Italy, 2007
Coauthor Index

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last updated on 2025-10-28 23:38 CET by the dblp team
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