Lorenzo Tamellini

31 papers Journal 31

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	Noise-robust multi-fidelity surrogate modelling for parametric partial differential equations. J. Comput. Phys. Benjamin M. Kent, Lorenzo Tamellini, Matteo Giacomini, Antonio Huerta
2026	J	`jnl`	Towards uncertainty quantification of a model for cancer-on-chip experiments. CoRR Silvia Bertoluzza, Vittoria Bianchi, Gabriella Bretti, Lorenzo Tamellini, Pietro Zanotti
2025	J	`jnl`	A Surrogate-Informed Framework for Sparse Grid Interpolation. CoRR Matteo Rosellini, Filippo Fruzza, Alessandro Mariotti, Maria-Vittoria Salvetti, Lorenzo Tamellini
2025	J	`jnl`	Democratizing uncertainty quantification. J. Comput. Phys. Linus Seelinger, Anne Reinarz, Mikkel Bue Lykkegaard, Robert Akers, Amal Mohammed A. Alghamdi, David Aristoff, Wolfgang Bangerth, Jean Bénézech, Matteo Diez, Kurt Frey, John D. Jakeman, Jakob Sauer Jørgensen, Ki-Tae Kim, Benjamin M. Kent, Massimiliano Martinelli, Matthew D. Parno, Riccardo Pellegrini, Noemi Petra, Nicolai André Brogaard Riis, Katherine Rosenfeld, Andrea Serani, Lorenzo Tamellini, Umberto Villa, Tim J. Dodwell, Robert Scheichl
2025	J	`jnl`	Noise-robust multi-fidelity surrogate modelling for parametric partial differential equations. CoRR Benjamin M. Kent, Lorenzo Tamellini, Matteo Giacomini, Antonio Huerta
2024	J	`jnl`	Algorithm 1040: The Sparse Grids Matlab Kit - a Matlab implementation of sparse grids for high-dimensional function approximation and uncertainty quantification. ACM Trans. Math. Softw. Chiara Piazzola, Lorenzo Tamellini
2024	J	`jnl`	An efficient slope stability algorithm with physically consistent parametrisation of slip surfaces. CoRR Leonardo Maria Lalicata, Andrea Bressan, Simone Pittaluga, Lorenzo Tamellini, Domenico Gallipoli
2024	J	`jnl`	Democratizing Uncertainty Quantification. CoRR Linus Seelinger, Anne Reinarz, Mikkel Bue Lykkegaard, Amal Mohammed A. Alghamdi, David Aristoff, Wolfgang Bangerth, Jean Bénézech, Matteo Diez, Kurt Frey, John D. Jakeman, Jakob Sauer Jørgensen, Ki-Tae Kim, Massimiliano Martinelli, Matthew D. Parno, Riccardo Pellegrini, Noemi Petra, Nicolai André Brogaard Riis, Katherine Rosenfeld, Andrea Serani, Lorenzo Tamellini, Umberto Villa, Tim J. Dodwell, Robert Scheichl
2024	J	`jnl`	Two Nitsche-based mixed finite element discretizations for the seepage problem in Richards' equation. CoRR Federico Gatti, Andrea Bressan, Alessio Fumagalli, Domenico Gallipoli, Leonardo Maria Lalicata, Simone Pittaluga, Lorenzo Tamellini
2023	J	`jnl`	Comparing multi-index stochastic collocation and multi-fidelity stochastic radial basis functions for forward uncertainty quantification of ship resistance. Eng. Comput. Chiara Piazzola, Lorenzo Tamellini, Riccardo Pellegrini, Riccardo Broglia, Andrea Serani, Matteo Diez
2023	J	`jnl`	Data-informed uncertainty quantification for laser-based powder bed fusion additive manufacturing. CoRR Mihaela Chiappetta, Chiara Piazzola, Lorenzo Tamellini, Alessandro Reali, Ferdinando Auricchio, Massimo Carraturo
2023	J	`jnl`	Lowering the Entry Bar to HPC-Scale Uncertainty Quantification. CoRR Linus Seelinger, Anne Reinarz, Jean Bénézech, Mikkel Bue Lykkegaard, Lorenzo Tamellini, Robert Scheichl
2022	J	`jnl`	Combining noisy well data and expert knowledge in a Bayesian calibration of a flow model under uncertainties: an application to solute transport in the Ticino basin. CoRR Emily A. Baker, Sauro Manenti, Alessandro Reali, Giancarlo Sangalli, Lorenzo Tamellini, Sara Todeschini
2022	J	`jnl`	Combining the Morris Method and Multiple Error Metrics to Assess Aquifer Characteristics and Recharge in the Lower Ticino Basin, in Italy. CoRR Emily A. Baker, Alessandro Cappato, Sara Todeschini, Lorenzo Tamellini, Giancarlo Sangalli, Alessandro Reali, Sauro Manenti
2022	J	`jnl`	Inverse and forward sparse-grids-based uncertainty quantification analysis of laser-based powder bed fusion of metals. CoRR Mihaela Chiappetta, Chiara Piazzola, Massimo Carraturo, Lorenzo Tamellini, Alessandro Reali, Ferdinando Auricchio
2022	J	`jnl`	On the Convergence of Adaptive Stochastic Collocation for Elliptic Partial Differential Equations with Affine Diffusion. SIAM J. Numer. Anal. Martin Eigel, Oliver G. Ernst, Björn Sprungk, Lorenzo Tamellini
2022	J	`jnl`	The Sparse Grids Matlab kit - a Matlab implementation of sparse grids for high-dimensional function approximation and uncertainty quantification. CoRR Chiara Piazzola, Lorenzo Tamellini
2022	J	`jnl`	Uncertainty quantification in timber-like beams using sparse grids: theory and examples with off-the-shelf software utilization. CoRR Giuseppe Balduzzi, Francesca Bonizzoni, Lorenzo Tamellini
2021	J	`jnl`	Comparing Multi-Index Stochastic Collocation and Multi-Fidelity Stochastic Radial Basis Functions for Forward Uncertainty Quantification of Ship Resistance. CoRR Chiara Piazzola, Lorenzo Tamellini, Riccardo Pellegrini, Riccardo Broglia, Andrea Serani, Matteo Diez
2020	J	`jnl`	Compressive Isogeometric Analysis. CoRR Simone Brugiapaglia, Lorenzo Tamellini, Mattia Tani
2020	J	`jnl`	Compressive isogeometric analysis. Comput. Math. Appl. Simone Brugiapaglia, Lorenzo Tamellini, Mattia Tani
2020	J	`jnl`	Computational Approaches for Uncertainty Quantification of Naval Engineering Problems. ERCIM News Riccardo Broglia, Matteo Diez, Lorenzo Tamellini
2020	J	`jnl`	On the convergence of adaptive stochastic collocation for elliptic partial differential equations with affine diffusion. CoRR Martin Eigel, Oliver G. Ernst, Björn Sprungk, Lorenzo Tamellini
2020	J	`jnl`	Uncertainty Quantification of Ship Resistance via Multi-Index Stochastic Collocation and Radial Basis Function Surrogates: A Comparison. CoRR Chiara Piazzola, Lorenzo Tamellini, Riccardo Pellegrini, Riccardo Broglia, Andrea Serani, Matteo Diez
2019	J	`jnl`	On Expansions and Nodes for Sparse Grid Collocation of Lognormal Elliptic PDEs. CoRR Oliver G. Ernst, Björn Sprungk, Lorenzo Tamellini
2019	J	`jnl`	Parametric shape optimization for combined additive-subtractive manufacturing. CoRR Christian Altenhofen, Marco Attene, Oliver J. D. Barrowclough, Michele Chiumenti, Marco Livesu, Federico Marini, Massimiliano Martinelli, Vibeke Skytt, Lorenzo Tamellini
2018	J	`jnl`	Convergence of Sparse Collocation for Functions of Countably Many Gaussian Random Variables (with Application to Elliptic PDEs). SIAM J. Numer. Anal. Oliver G. Ernst, Björn Sprungk, Lorenzo Tamellini
2016	J	`jnl`	Convergence of quasi-optimal sparse-grid approximation of Hilbert-space-valued functions: application to random elliptic PDEs. Numerische Mathematik Fabio Nobile, Lorenzo Tamellini, Raúl Tempone
2016	J	`jnl`	Multi-index Stochastic Collocation Convergence Rates for Random PDEs with Parametric Regularity. Found. Comput. Math. Abdul-Lateef Haji-Ali, Fabio Nobile, Lorenzo Tamellini, Raúl Tempone
2014	J	`jnl`	Convergence of quasi-optimal Stochastic Galerkin methods for a class of PDES with random coefficients. Comput. Math. Appl. Joakim Beck, Fabio Nobile, Lorenzo Tamellini, Raúl Tempone
2014	J	`jnl`	Model Reduction Based on Proper Generalized Decomposition for the Stochastic Steady Incompressible Navier-Stokes Equations. SIAM J. Sci. Comput. Lorenzo Tamellini, Olivier P. Le Maître, Anthony Nouy