Lorenzo Tamellini

According to our database, Lorenzo Tamellini authored at least 23 papers between 2014 and 2025.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2025

Democratizing uncertainty quantification.

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

J. Comput. Phys., 2025

2024

Algorithm 1040: The Sparse Grids Matlab Kit - a Matlab implementation of sparse grids for high-dimensional function approximation and uncertainty quantification.

Chiara Piazzola, Lorenzo Tamellini

ACM Trans. Math. Softw., March, 2024

Two Nitsche-based mixed finite element discretizations for the seepage problem in Richards' equation.

Federico Gatti, Andrea Bressan, Alessio Fumagalli, Domenico Gallipoli, Leonardo Maria Lalicata, Simone Pittaluga, Lorenzo Tamellini

CoRR, 2024

Democratizing Uncertainty Quantification.

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

CoRR, 2024

2023

Comparing multi-index stochastic collocation and multi-fidelity stochastic radial basis functions for forward uncertainty quantification of ship resistance.

Chiara Piazzola, Lorenzo Tamellini, Riccardo Pellegrini, Riccardo Broglia, Andrea Serani, Matteo Diez

Eng. Comput., 2023

Data-informed uncertainty quantification for laser-based powder bed fusion additive manufacturing.

Mihaela Chiappetta, Chiara Piazzola, Lorenzo Tamellini, Alessandro Reali, Ferdinando Auricchio, Massimo Carraturo

CoRR, 2023

Lowering the Entry Bar to HPC-Scale Uncertainty Quantification.

Linus Seelinger, Anne Reinarz, Jean Bénézech, Mikkel Bue Lykkegaard, Lorenzo Tamellini, Robert Scheichl

CoRR, 2023

2022

On the Convergence of Adaptive Stochastic Collocation for Elliptic Partial Differential Equations with Affine Diffusion.

Martin Eigel, Oliver G. Ernst, Björn Sprungk, Lorenzo Tamellini

SIAM J. Numer. Anal., 2022

Uncertainty quantification in timber-like beams using sparse grids: theory and examples with off-the-shelf software utilization.

Giuseppe Balduzzi, Francesca Bonizzoni, Lorenzo Tamellini

CoRR, 2022

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.

Emily A. Baker, Sauro Manenti, Alessandro Reali, Giancarlo Sangalli, Lorenzo Tamellini, Sara Todeschini

CoRR, 2022

Inverse and forward sparse-grids-based uncertainty quantification analysis of laser-based powder bed fusion of metals.

Mihaela Chiappetta, Chiara Piazzola, Massimo Carraturo, Lorenzo Tamellini, Alessandro Reali, Ferdinando Auricchio

CoRR, 2022

Combining the Morris Method and Multiple Error Metrics to Assess Aquifer Characteristics and Recharge in the Lower Ticino Basin, in Italy.

Emily A. Baker, Alessandro Cappato, Sara Todeschini, Lorenzo Tamellini, Giancarlo Sangalli, Alessandro Reali, Sauro Manenti

CoRR, 2022

The Sparse Grids Matlab kit - a Matlab implementation of sparse grids for high-dimensional function approximation and uncertainty quantification.

Chiara Piazzola, Lorenzo Tamellini

CoRR, 2022

2020

Computational Approaches for Uncertainty Quantification of Naval Engineering Problems.

Riccardo Broglia, Matteo Diez, Lorenzo Tamellini

ERCIM News, 2020

Uncertainty Quantification of Ship Resistance via Multi-Index Stochastic Collocation and Radial Basis Function Surrogates: A Comparison.

Chiara Piazzola, Lorenzo Tamellini, Riccardo Pellegrini, Riccardo Broglia, Andrea Serani, Matteo Diez

CoRR, 2020

Compressive isogeometric analysis.

Simone Brugiapaglia, Lorenzo Tamellini, Mattia Tani

Comput. Math. Appl., 2020

2019

Parametric shape optimization for combined additive-subtractive manufacturing.

Christian Altenhofen, Marco Attene, Oliver J. D. Barrowclough, Michele Chiumenti, Marco Livesu, Federico Marini, Massimiliano Martinelli, Vibeke Skytt, Lorenzo Tamellini

CoRR, 2019

On Expansions and Nodes for Sparse Grid Collocation of Lognormal Elliptic PDEs.

Oliver G. Ernst, Björn Sprungk, Lorenzo Tamellini

CoRR, 2019

2018

Convergence of Sparse Collocation for Functions of Countably Many Gaussian Random Variables (with Application to Elliptic PDEs).

Oliver G. Ernst, Björn Sprungk, Lorenzo Tamellini

SIAM J. Numer. Anal., 2018

2016

Convergence of quasi-optimal sparse-grid approximation of Hilbert-space-valued functions: application to random elliptic PDEs.

Fabio Nobile, Lorenzo Tamellini, Raúl Tempone

Numerische Mathematik, 2016

Multi-index Stochastic Collocation Convergence Rates for Random PDEs with Parametric Regularity.

Abdul-Lateef Haji-Ali, Fabio Nobile, Lorenzo Tamellini, Raúl Tempone

Found. Comput. Math., 2016

2014

Model Reduction Based on Proper Generalized Decomposition for the Stochastic Steady Incompressible Navier-Stokes Equations.

Lorenzo Tamellini, Olivier P. Le Maître, Anthony Nouy

SIAM J. Sci. Comput., 2014

Convergence of quasi-optimal Stochastic Galerkin methods for a class of PDES with random coefficients.

Joakim Beck, Fabio Nobile, Lorenzo Tamellini, Raúl Tempone

Comput. Math. Appl., 2014