Toni Lassila

Statistical and Nonlinear Physics · 2014

A researcher in the Science corpus: 1 paper; trusts 25 researchers and is trusted by 2 researchers here, as inferred from the citation graph.

Subfields

• Statistical and Nonlinear Physics — 41 citations into it; #8,457 of 10,127 by trust here, #7,402 by citations
• Computational Mechanics — 40 citations into it
• Statistics and Probability — 20 citations into it
• Numerical Analysis — 15 citations into it; #3,132 of 3,586 by trust here, #2,107 by citations
• Mechanics of Materials — 9 citations into it
• Computational Theory and Mathematics — 8 citations into it

Whom Toni Lassila trusts overall

Their strongest outbound trust, strongest first, inferred from their citations.

1. Anthony T. Patera
2. Dacian N. Daescu
3. Karen Veroy
4. David Amsallem
5. Bernard Haasdonk
6. Clarence W. Rowley
7. Gianluigi Rozza
8. Athanasios C. Antoulas
9. David J. Knezevic
10. Ngoc Cuong Nguyen

Who trusts Toni Lassila overall

1. Andrea Manzoni
2. Stefano Lorenzi
3. Francesco Ballarin
4. Jared D. Willard
5. Gianluigi Rozza
6. Antonio Cammi

Papers from Toni Lassila's perspective

Ordered by how strongly the researchers Toni Lassila trusts endorse each paper. Same corpus, a different order for every researcher.

1. An ‘empirical interpolation’ method: application to efficient reduced-basis discretization of partial differential equations
2. A posteriori error bounds for reduced-basis approximations of parametrized parabolic partial differential equations
3. Balanced Model Reduction via the Proper Orthogonal Decomposition
4. Certified real‐time solution of the parametrized steady incompressible Navier–Stokes equations: rigorous reduced‐basis a posteriori error bounds
5. Approximation of Large-Scale Dynamical Systems (Advances in Design and Control)
6. A subspace approach to balanced truncation for model reduction of nonlinear control systems
7. Model Reduction for fluids, Using Balanced Proper Orthogonal Decomposition (International Journal of Bifurcation and Chaos in Applied Sciences and Engineering)
8. EFFICIENT REDUCED-BASIS TREATMENT OF NONAFFINE AND NONLINEAR PARTIAL DIFFERENTIAL EQUATIONS
9. Numerical Approximation of Partial Differential Equations
10. REDUCED BASIS METHOD FOR FINITE VOLUME APPROXIMATIONS OF PARAMETRIZED LINEAR EVOLUTION EQUATIONS

Their papers

• Model Order Reduction in Fluid Dynamics: Challenges and Perspectives (2014) — 291 citations